METHOD AND DEVICE FOR MONITORING AND ESTIMATING PARAMETERS RELATING TO THE FLIGHT OF AN AIRCRAFT.

专利摘要:
- Method and device for monitoring and estimating parameters relating to the flight of an aircraft. The device 1 for monitoring and estimating parameters relating to the flight of an aircraft comprises an estimation module 4 for determining an estimate of the values of the parameters relating to the flight of the aircraft and for generating residues; detection 5 to determine the statuses associated with each of said sensors C1, C2, CN and a parameter P1 corresponding to the mass of the aircraft, a transmission module 5 for transmitting the status associated with each of said sensors C1, C2, .. ., CN to a user device 6 and, at the next iteration, to the estimation module 4.
公开号:FR3066755A1
申请号:FR1754549
申请日:2017-05-23
公开日:2018-11-30
发明作者:Guillaume Alcalay；Martin Delporte；Philippe Goupil；Cedric Seren；Georges HARDIER
申请人:Office National dEtudes et de Recherches Aerospatiales ONERA；Airbus Operations SAS；
IPC主号:

专利说明:

TECHNICAL AREA
The present invention relates to a method and an associated device for monitoring and estimating parameters relating to the flight of an aircraft in real time.
STATE OF THE ART
The proper functioning of an aircraft is partly guaranteed by that of the sensors. They provide information on his attitude, trajectory, speed, etc. and enable navigation, guidance and control of the latter via control laws and servo algorithms. The high levels of automation available today on some aircraft depend on the availability of these sensors. Today, any loss of information due to sensor failures puts pilots more in control of the aircraft, which increases their workload. In order to facilitate the piloting task, it is therefore necessary to extend the availability of flight parameters and this for the entire duration of the flight. This involves using a step to validate the quality of the information provided by the sensors, called "monitoring".
In order to ensure better sensor monitoring and to increase the availability of flight parameters in the event of a breakdown, two types of approach have been addressed.
A first type of approach corresponds to the use of hardware redundancies, that is to say to the use of several sensors of the same type in order to allow the identification of faults via in particular a majority-based vote (for example an average calculation or the choice of the median value). This first type of approach involves increasing the number of on-board sensors, which in the case of poorly instrumented aircraft is not realistic. In addition, in the event of coherent and perfectly simultaneous failures of the various sensors, majority-based voting does not allow a fault to be identified. This is called the common failure mode.
A second type of approach corresponds to the use of analytical redundancy. Sensor measurements can be linked through kinematic equations and flight mechanics. These interdependent relationships between measurements and parameters relating to flight have the advantage of being able to increase the dissimilarity of information through the use of virtual sensors. These virtual sensors deliver parameter and measurement estimates calculated from combinations of sensors measuring quantities of different types. The advantage of this approach is that it does not increase the number of sensors necessary for monitoring since it uses only the information already present on board the aircraft. However, it may require the availability of sufficient on-board computing resources. Analytical redundancy is used when developing estimators. These estimators also have the advantage of being able to deliver an estimate of the quantity invalidated after failure in order to guarantee greater availability of the flight parameters.
The problems that arise today relate to both types of approach. First, the use of majority-based voting does not allow full monitoring of common failure modes. Then the analytical redundancy is based on assumptions of validity of certain quantities, or of other sensors. It is necessary that these hypotheses are verified and that the algorithm developed is validated.
One of the problems that we also seek to solve is that of the dissociation of a breakdown on the incidence, a breakdown on the speed and an error on the mass in addition to the problem of estimation. Many estimators have been developed to date, but none allow to approach the problem with hypotheses allowing to make this distinction.
STATEMENT OF THE INVENTION
The object of the present invention is to overcome this drawback by proposing a method and a device for monitoring and estimating parameters relating to the flight of an aircraft.
Flight parameters include at least one of the following: flight parameters, atmospheric parameters, sensor bias, or modeling bias. To this end, the invention relates to a monitoring and estimation process: - of parameters relating to the flight of an aircraft; - sensor statuses, these statuses being representative of an operation of said sensors; and - a status of a parameter corresponding to the current mass of the aircraft, this status being representative of the validity of said parameter.
According to the invention, the method comprises the following steps: - an initialization step, implemented by an initialization module, consisting in initializing the statuses of sensors configured to determine flight parameters of the aircraft as well as the status of the parameter corresponding to the current mass of the aircraft and to initialize parameters used during the implementation of the monitoring and estimation device; the method further comprising the following steps, implemented iteratively: - an estimation step, implemented by an estimation module, consisting in determining an estimate of the values of the parameters relating to the flight of the aircraft as well an estimate of an error of the current mass parameter, from: o measurements of the parameters relating to the flight provided by the sensors, o parameters relating to the flight initialized in the initialization step or estimated at the iteration preceding the estimation step and o the statuses associated with each of said sensors, the estimation step also consisting in generating residues which are a function of the values of the parameters relating to the flight measured and estimated and of terms of innovation which correspond to the difference between a measured flight parameter value and said estimated value; a first transmission step, implemented by a first transmission module, consisting of: transmitting to a user device and to a detection module a signal representative of the estimation of the values of the parameters relating to the flight of the aircraft as well as the estimation of the error of the current mass parameter, determined in the estimation step, o to send to said detection module a signal representative of the residues generated in the estimation step; a detection step, implemented by a detection module, consisting in determining the different statuses associated with each of said sensors and with the parameter corresponding to the current mass of the aircraft, from: o the estimation of the values of the residues determined in the estimation step, o the estimation of the values of the parameters relating to the flight of the aircraft determined in the estimation step, o measurements of the parameters relating to the flight provided by the sensors, o the estimation of the error of the current mass parameter determined in the estimation step, and o of the statuses determined in the previous iteration of the detection step or initialized in the initialization step, - a second transmission step, implemented by a second transmission module, consisting in transmitting to the user device and, on the next iteration, to the estimation module the various s statuses associated with each of said sensors and the status associated with said parameter corresponding to the current mass.
Thanks to the invention, it is possible to identify sensor failures and a mass error in an on-board system of an aircraft. It also makes it possible to continuously supply an estimate of the parameters relating to the flight of the aircraft in real time as well as a status of the various sensors and of the parameter corresponding to the mass.
In addition, the estimation step comprises the following sub-steps: - an adaptation sub-step, implemented by an adaptation sub-module, consisting in determining a variance and / or an associated validity boolean to each of the measurements of the flight-related parameters provided by the sensors as well as of the adjustment parameters associated with the estimation algorithm used in an estimation sub-step, from: o said measurements of the flight-related parameters, and o statuses associated with each of said sensors; the adaptation sub-step also consisting in correcting the current mass from a mass error estimated at the previous iteration or initialized at the initialization step, and from a status associated with the parameter corresponding to the mass, the estimation sub-step, implemented by an estimation sub-module, consisting in determining the estimate of the values of the parameters relating to the flight as well as an estimate of the error of said mass from: measurements of the parameters relating to the flight provided by said sensors, o of the parameters relating to the flight estimated at the previous iteration or initialized at the initialization step and o from the variance and / or the boolean of validity of each of the measurements of the parameters relating to the flight and of the adjustment parameters determined in the adaptation sub-step, the estimation sub-step also consisting in generating the residues from the para estimated and measured flight-related meters and terms of innovations.
In addition, the detection step comprises the following sub-steps: - a sub-step for detecting a faulty sensor and erroneous flight parameters, implemented by a detection sub-module, consisting in determining: o the common status associated with the sensor configured to measure the angle of incidence of the aircraft and with the parameter corresponding to the current mass and o the status associated with the other sensors, from: o measurements of the parameters relating to the flight provided by said sensors , o the estimation of the values of the parameters relating to the flight as well as the mass error, o the statuses associated with each of said sensors and with the parameter corresponding to a current aircraft mass determined at the previous iteration or initialized at the initialization step and o residues; - a sub-step for validating the angle of incidence and the current mass, implemented by a validation sub-module, consisting in determining the status associated with the parameter corresponding to the current mass and the status associated with the sensor configured to measure the angle of incidence (a), from: o the common status associated with the sensor configured to measure the angle of incidence of the aircraft and the parameter corresponding to the current mass, o the statuses associated with other sensors, o estimated flight parameters, o estimated mass error, o measured flight parameters, o residuals generated in the estimation sub-step and o a lift coefficient supplied to from an on-board modeling supplied with the flight parameters estimated and measured by the sensors.
Thus, it is possible to distinguish a fault between the incidence angle measurement and the parameter corresponding to the mass, including in the case of common failure modes.
According to a first embodiment, the estimation sub-step corresponds to an extended Kalman filter associated with a state vector, an observation vector and an auxiliary measurement vector, the auxiliary measurement vector having as expression: Z = 5spim 'Ψπρ θπν ^ Xljn> COnf, Vgyo Vg7o zgm)' in which: - iHm corresponds to a measure of deflection of the horizontal plane, - ôqi ^ corresponds to a measure of deflection of elevators of the aircraft, - ôsp. ^ corresponds to a measure of deflection of the aircraft's spoilers, - ψ ™ corresponds to a heading measurement, - <pm corresponds to a tilt angle measurement, - 0m corresponds to a tilt measurement, - nx corresponds to a measurement of longitudinal load factor in the coordinate system linked to the aircraft, - m corresponds to the current mass parameter of the aircraft, - conf corresponds to a measurement of the aerodynamic configuration of the aircraft,
correspond to measurements of the ground speed components in the terrestrial frame of reference, and - zg ^ corresponds to a measurement of geometric altitude; the state vector presenting as expression:
in which: - (WXo, Wyo, WZo) correspond to the three components of the wind speed in the terrestrial coordinate system, - AISA corresponds to a difference in temperature between a current static temperature and a temperature determined from a model of standard atmosphere at a current geometric altitude, - bCt corresponds to a modeling bias of the lift coefficient, and - Cbx corresponds to a barometric correction term; the derivative of the state vector presenting as expression:
in which, xb corresponds to a characteristic time associated with a dynamic of the modeling bias of the lift coefficient bCL, the observation vector presenting as expression:
in which: - am corresponds to an incidence measurement, - pm corresponds to a skid measurement, - PSm corresponds to a static pressure measurement, - nZm corresponds to a measurement of vertical load factor in a reference linked to the aircraft, - PTm corresponds to a total pressure measurement, - TTm corresponds to a total temperature measurement, and - zp corresponds to the pressure altitude and is expressed according to the equation zp = Âïs - Cbxi with T15 = 288.15 K, F l + T— T15 - ζ corresponds to a function linking the measurement of the altitude pressure zp to the static pressure with the following expression: ίζ (Ζρ „> ZPll) = iO108 ·» ^ ·· '1 Rt / LsM <Zp ") = Pü (l - ^ ζΡη,) Γ ° τ '" in which: - zPii = 11 km corresponds to the standard altitude of the tropopause, - Ρ41 = 226,321 mbar and 7 ^ = 216.65 K correspond to the standard static pressure and static temperature at the tropopause, - GTzo = 0.0065 K / m the standard temperature gradient for zP m <ZPll ’
- g at the acceleration of gravity, - R the specific air constant, - Ts corresponds to the statistical temperature parameter and is expressed according to the equation Ts = To + GTzozg + AISA, with To = 273.15 K and GT n = 0.0065 K / m, - V corresponds to the air speed flight parameter and is expressed according to the equation V = Vu2 + v2 + w2, with each component of the air speed defined in the coordinate system aircraft (u, v, w) expressed according to the following expression:
cos θ cos ψ cos θ sin ψ sinO Vgxo - VV
= sin φ sin θ cos ψ - cos φ sin ψ sin φ sin θ sin ψ + cos φ cos ψ - sin φ cos θ Vgyo - VV _cos φ sin θ cos ψ + sin φ sin ψ cos φ sin θ cos ψ + sin φ sin ψ - coscpcosOj y - WL θζο - M corresponds to the flight parameter of the Mach number calculated according to the norm of the air speed V according to the equation M = - ^ = with r corresponding to the specific constant of the air, the estimation sub-step generating at an iteration k the following residues: - a first residue having as expression at a time tk =
in which: ° £ "(tk) corresponds to the innovation term associated with the measurement of the angle of incidence a at time tk, where bCz corresponds to an estimation of the modeling bias of the lift coefficient Cz at time tk, and o CZa (conf (tk)) corresponds to a tabulated value of the lift coefficient depending on a value of a configuration parameter of the aircraft at time tk,
- a second residue having as expression at time tk r2 (tk) =
in which: ο γ corresponds to the adiabatic coefficient of air, o TTm corresponds to a total temperature measured by one of the sensors used at the input of the estimation module, o PTm corresponds to a total pressure measured by one of the sensors used at input of the estimation module, o zPm corresponds to a pressure altitude measured by one of the sensors used at the input of the estimation module, ο ζ corresponds to the function linking the measurement of the pressure altitude to the static pressure and o Ts (zPjn , tk) corresponds to an estimate of the static temperature calculated from flight parameters estimated at time tk at the current iteration and at time tk_! to a previous iteration according to the first residue according to the formula:
Ts (zPm, tk) = T15 + GTzo (zPm (tk) + £ (s) +
Cbx (tk_i) (l - ΠΓ ± (r, (tk)))]) + £ (s) [AÎSA (tk) nr ± (ri (tk)) + ÂÎSÀCtk.J ^ ln ^ Crrttk)))], where L is the transfer function of a low-pass filter and nr ± (r) = H ^ r + y) - where H is the function of
Heaviside, and rf corresponds to the limits associated with the residue defined in the following description; - a third residue having as expression at time tk r3 (tk) =
in which: o m corresponds to the mass of the aircraft,
o S corresponds to the reference surface of the aircraft, og corresponds to the acceleration of gravity, o nZim corresponds to a vertical load factor, o nXim corresponds to a longitudinal load factor, o C, corresponds to the coefficient of estimated lift, obtained from estimated and measured flight parameters and aircraft configuration.
According to a first variant, the observation vector has as expression:
in which: - pT,> „a corresponds to a total pressure value from an engine-nacelle modeling eng, - Ps„ „„ corresponds to a static pressure value from the engine-nacelle modeling cng, and - TT a measured value of total temperature from a sensor of 1 engrr total engine-nacelle temperature;
the estimation sub-step further generating the following residues: - a fourth residue having the expression r4 (tk) = εΡτ (tk) in which spTeng (tk) corresponds to the difference between the total pressure value measured and said value of total pressure from modeling at a time (tk), - a fifth residue having the expression r5 (tk) = εΡδ (tk) in which £ Pseng (tk) corresponds to the difference between the measured value of static pressure and said value of static pressure resulting from the modeling at a time (tk), and - a sixth residue having for expression r6 (tk) = εΤΑΤ (tk) in which £ TAT ", 1„ (tk) corresponds to the difference between the value total temperature measurement and said total temperature value from the engine-nacelle measurement at a time (tk).
The engine-nacelle modeling is described in patent FR 2 977 942. It makes it possible to deduce therefrom the two virtual measurements PSeng and PT useful for this patent. In summary, the static pressure Ρς obtained is made up of digital data corresponding to the measurements of static pressures of the ambient air in the nacelle Pnac while the total pressure PT obtained is deduced from the data entry corresponding to the measurements of static pressures of the ambient air in the Pnac nacelle, the "engine" static pressure Pmot, the speed of rotation of the engine blower and the measurement of the total air temperature.
According to a second variant, the estimation sub-step corresponds to an extended Kalman filter associated with a state vector and an observation vector and an auxiliary measures vector, the auxiliary measures vector having as expression:
in which nYim corresponds to a measurement of lateral load factor in the coordinate system linked to the aircraft, the state vector having as expression:
in which: - vgxo'Vgyo'Vgzo correspond to the three components of the ground speed in the terrestrial coordinate system, - bn, bn, bn correspond to the three components of accelerometer bias in the coordinate system linked to the aircraft, - zG corresponds to a geometric altitude; the derivative of the state vector presenting as expression:
in which: - Mrot corresponds to a usual rotation matrix from the terrestrial frame to the frame linked to the aircraft and has for expression Mrot - (cosθcosψ sin φ sin θ cos ψ - cos φ sin ψ cos φ sin θ οο5ψ + sin φ 5ίηψ cos θ sin ψ sin φ sin θ sin ψ + cos φ cos ψ cos φ sin θ sin ψ - sin φ cos ψ), sin θ - sin φ cos0 - cos φ cos θ / the observation vector presenting as expression :
in which: - V „, V„, V „corresponds to measurements of three components of gxom gyom’ gxom r r ground speed, and - zGm corresponds to a measurement of geometric altitude.
According to a third variant, the lateral component v of the air speed V is assumed to be zero.
This means that the wander β is assumed to be zero.
Furthermore, the determination of the common status and of the status associated with the other sensors of the faulty sensor detection sub-step comprises the following sub-steps: - a sub-step for assigning to each residue a maximum limit and a minimum limit from estimated flight parameters; - the sub-step also being a sub-step for building a first validity indicator associated with the static pressure sensor and a second validity sensor associated with the pressure sensor
total from the estimated parameters and measurements from the aircraft sensors: o the first validity indicator equal to 1 if the relation | £ h (s) (zPm - zGJ | <lPs is verified, the first validity indicator equal 0 if the relation | £ h (s) (zPm - zGJ | <lPs is not verified, in which lPg corresponds to a limit determined experimentally as a function of the dynamics of the aircraft, £ h corresponding to the transfer function d 'a high-pass filter, where the second validity indicator being worth 0 by default and 1 if the residue crosses its respective limits, at an instant tk, determined subsequently and that 3n e M such that tn e [tk -xPT, tk] satisfying | (1 - £ x) (MpT (tn) - ΜΡτ (ΐη _ {)) | <1Pt, with τΡτ a time constant, £ x a transfer function of a low-pass filter having as constant of time τ, I M a constant, and 1Pt a limit determined experimentally according to the dynamics of the plane; indicators s of residue being calculated and associated with each residue and validity indicators; a sub-step for identifying the appearance of faults when the sum of the residual indicators is strictly greater than zero and identifying, in the event of a fault, the faulty sensor by comparing the current values of the residual indicators with those listed in a table, identified offline or online, listing the failure cases according to the different value combinations of the residue indicators.
According to a second embodiment, the statuses associated with each of said sensors are also determined from auxiliary statuses associated with each of said sensors capable of being sent to the detection module by a monitoring module.
According to a third embodiment, for a consolidated flight parameter measured from a plurality of sensors, the method comprises the following substeps implemented by a unit verification module, when a failure is detected for a sensor measuring said flight parameter, said measurement of which is used at the input of the estimation module: a reconfiguration sub-step of the estimation sub-module so as not to take into account the erroneous measurement of the flight parameter used hitherto in the estimation sub-step, a sub-step for calculating the difference between the estimation of said flight parameter and of the measurement of one of said sensors from the plurality of sensors, for each of the measurements from the plurality sensors, if the absolute value of the difference is less than a predetermined value, the measurement being retained in the estimation sub-step. The invention also relates to a monitoring and estimation device: - parameters relating to the flight of an aircraft; - sensor statuses, these statuses being representative of an operation of said sensors; and - a status of a parameter corresponding to the current mass of the aircraft, this status being representative of the validity of said parameter.
According to the invention, the monitoring and estimation device comprises: - an initialization module, configured to initialize the statuses of sensors configured to determine parameters relating to the flight of the aircraft as well as the status of the parameter corresponding to the current mass of the aircraft and to initialize parameters used during the implementation of the monitoring and estimation device; the monitoring and estimation device further comprises the following modules, implemented iteratively: - an estimation module, configured to determine an estimate of the values of the parameters relating to the flight of the aircraft as well as an estimation an error of the current mass parameter, from: o measurements of the flight-related parameters provided by the sensors, o flight-related parameters initialized in the initialization step or estimated on the previous iteration of the estimation step and o of the statuses associated with each of said sensors, the estimation module also being configured to generate residues which are a function of the values of the parameters relating to the flight measured and estimated and of innovation terms which correspond to the difference between a measured flight parameter value and said estimated value; a first transmission module configured to: o transmit to a user device and to a detection module a signal representative of the estimation of the values of the parameters relating to the flight of the aircraft as well as of the estimation of the error of the current mass parameter, determined in the estimation step, o send to said detection module a signal representative of the residues generated in the estimation step to said detection module; a detection module configured to determine the different statuses associated with each of said sensors and with the parameter corresponding to the current aircraft mass, from: o the estimation of the residue values determined in the estimation step, o estimation of the parameters of the parameters relating to the flight of the aircraft determined in the estimation step, o measurements of the parameters relating to the flight provided by the sensors, o estimation of the error of the mass parameter current determined by the estimation module, o of said statuses determined in the previous iteration or initialized in the initialization step. - a second transmission module configured to transmit to the user device and, on the next iteration, to the estimation module the different statuses associated with each of said sensors and the status associated with said parameter corresponding to the current mass.
In addition, the estimation module includes: - an adaptation sub-module configured to determine a variance and / or a boolean of validity associated with each of the measurements of the parameters relating to the flight provided by the sensors as well as adjustment parameters associated with the estimation algorithm used in an estimation sub-module, from: o said measurements of the parameters relating to the flight and o from the statuses associated with each of said sensors; the adaptation sub-module also being configured to correct the current mass from an estimate of a mass error obtained on the previous iteration or initialized by the initialization module, and from a status associated with the parameter corresponding to the mass, - the estimation sub-module configured to determine the estimate of the values of the parameters relating to the flight as well as an estimate of the error of said mass, from: o measurements of the parameters relating to the flight supplied by said sensors, o parameters relating to the flight estimated at the previous iteration or initialized in the initialization step and o from the variance and / or the boolean of validity of each of the measurements of the parameters relating to the flight and adjustment parameters determined in the adaptation sub-step, the estimation sub-module also being configured to generate residuals from the rela estimated and measured flight tif and innovations.
In addition, the detection module comprises: - a detection sub-module configured to determine: o the common status associated with the sensor configured to measure the angle of incidence of the aircraft and with the parameter corresponding to the current mass and o the status associated with the other sensors, based on: o measurements of the parameters relating to the flight provided by said sensors, o the estimation of the values of the parameters relating to the flight as well as the mass error, o the statuses associated with each said sensors and a parameter corresponding to a current mass of aircraft determined in the preceding iteration or initialized in the initialization step, and o of the residues; - a validation sub-module configured to determine the status associated with the parameter corresponding to the current mass and the status associated with the sensor configured to measure the angle, from: o the common status associated with the sensor configured to measure the angle d incidence of the aircraft and of the parameter corresponding to the current mass, o of the statuses associated with the other sensors, o of the parameters relating to the estimated flight, o of the estimated mass error, o of the parameters relating to the measured flight, o of the residues generated in the estimation sub-step and o of a lift coefficient provided from on-board modeling supplied by the parameters relating to the flight estimated and measured by said sensors. The invention also relates to an aircraft, in particular a transport aircraft, which comprises a device for monitoring and estimating flight parameters of an aircraft as described above.
BRIEF DESCRIPTION OF THE FIGURES The invention, with its characteristics and advantages, will emerge more clearly on reading the description made with reference to the appended drawings in which: - Figure 1 represents a block diagram of an embodiment of the monitoring device and estimation; - Figure 2 shows steps in the monitoring and estimation process; - Figure 3 shows sub-steps implemented in another embodiment in which the aircraft uses hardware redundancy; - Figure 4 shows a block diagram of the embodiment of the monitoring and estimation device in which the aircraft uses hardware redundancy; - Figure 5 shows an aircraft carrying the monitoring and estimation device.
DETAILED DESCRIPTION
The remainder of the description will refer to the figures cited above.
FIG. 1 illustrates an embodiment of the monitoring and estimation device 1 of parameters relating to the flight of an aircraft AC and of statuses associated with the operation of the sensors C1, C2, ..., CN and with the validity of a parameter P1 corresponding to the mass of said aircraft, which can be carried on an AC aircraft (FIG. 5). Said device is called "monitoring and estimation device" in the following description. The monitoring and estimation method is configured to implement a monitoring and estimation method.
The flight-related parameters correspond to at least one of the following parameters: flight parameters, atmospheric parameters, sensor bias parameters, modeling bias parameters.
The flight parameters correspond to the flight parameters measured directly by sensors and / or to the flight parameters recalculated from measured flight parameters and / or estimated flight parameters.
The measured flight parameters include, for example, the angle of incidence a of the aircraft AC, the static pressure Ps, the total pressure PT, the load factor nZi, etc. They are directly derived from sensor measurements.
The recalculated flight parameters include, for example, the mass of the aircraft AC, the Mach number, air speed, calibrated speed, etc.
The estimated flight parameters refer to any flight parameters resulting from an estimation result.
The atmospheric parameters correspond to the parameters associated with the atmospheric environment. Atmospheric parameters include, for example, wind speed, local pressure or temperature gradients, AISA temperature differences between a recalculated static temperature and a temperature modeled by the international standard atmosphere model.
The sensor bias parameters correspond to parameters allowing to know the bias of a measurement coming from a sensor.
The modeling bias parameters correspond to deviations due to numerical models that can include sequences of more or less approximate equations or interpolation tables.
The monitoring and estimation device 1 comprises an initialization module COMP1 3 configured to initialize the statuses of sensors C1, C2, ... CN, of the parameter P1 corresponding to the mass of the aircraft AC and of the parameters used during of the implementation of the monitoring and estimation device 1. For example, the initialization can correspond at least to the fact that the statuses of all the sensors C1, C2, ... CN are considered to be statuses representative of the correct operation of said sensors C1, C2, ... CN. The parameters used during the implementation of the device 1 may include the parameters relating to the flight or intermediate parameters relating to the operation of the on-board algorithms during the implementation of the device 1.
The monitoring and estimation device 1 also comprises at least the following modules which are implemented iteratively: - an estimation module COMP2 4 (COMP for "computational module" in English); and - a COMP3 5 detection module.
The estimation module 4 is configured to determine an estimate of the values of the parameters relating to the flight of the aircraft AC from: - measurements of the parameters relating to the flight provided by the sensors C1, C2, ... CN, - parameters relating to the flight estimated at the previous iteration or initialized by the initialization module 3 and - of statuses associated with each of said sensors C1, C2, ... CN.
The estimation module 4 is also configured to generate residues which are a function of the values of the measured and estimated flight parameters and of innovation terms which correspond to the difference between a measured flight parameter value and said estimated value.
FIG. 1 represents a set 2 of N sensors C1, C2, ... CN. o The detection module 5 is configured to determine the different statuses associated with each of said sensors C1, C2, ... CN, with a parameter P1 corresponding to a current mass of aircraft AC, as well as an estimate of an error of said current mass. The different statuses, the parameter P1 and the error estimate are determined from: said residues determined by the estimation module 4, o of estimated and measured parameters relating to the flight of the aircraft as well as the estimation of the mass error, determined by the estimation module 4, o of said statuses determined in the previous iteration or initialized by the initialization module 3.
The monitoring and estimation device 1 also comprises a first TRANSI transmission module 7 (TRANS for "transmission module" in English) configured to: - transmit to a user device 6 and to the detection module 5 a signal representative of the estimation of the values of the parameters relating to the flight of the aircraft AC and of the mass error, determined by the estimation module 4, and - sending to the detection module 5 a signal representative of the residues generated by the estimation module 4.
The monitoring and estimation device 1 also comprises a second transmission module TRANS2 8 configured to transmit to the user device 6 and to the estimation module 4 the different statuses associated with each of said sensors C1, C2, ... CN, audit parameter P1 corresponding to the mass. The transmission of the statuses to the estimation module 4 is carried out in the following iteration.
This monitoring and estimation device 1 tackles the problem of being able to distinguish a fault between the different sensors C1, C2, ... CN and the parameter P1 corresponding to the current mass used at the input of the device monitoring and estimation 1, and more specifically a fault between the incidence, mass and speed, including in the case of common failure modes. It makes it possible to continuously deliver an estimate of the parameters relating to the flight of the aircraft AC in real time, including its mass, as well as a status of the various anemometric and clinometric sensors.
The estimation module 4 can include the following sub-modules: - an adaptation sub-module COMP21 41; and - a COMP22 42 estimation sub-module.
The adaptation sub-module 41 is configured to determine a variance and / or a boolean of validity associated with each of the measurements of the parameters relating to the flight provided by the sensors C1, C2, ... CN as well as associated adjustment parameters to the estimation algorithm used in the estimation sub-module 42. The determination is carried out from said measurements of the parameters relating to the flight and from the statuses associated with each of said sensors C1, C2, ... CN. The adaptation sub-module 41 is also configured to correct the current mass as a function of the mass error estimated at the previous iteration or initialized by the initialization module 3, and the status associated with the parameter P1 corresponding to the mass.
The variances and / or the booleans of validity are determined for flight parameter measurements provided by sensors C1, C2, ... CN whose statuses are representative of an operation of the sensors C1, C2, ... CN.
The adaptation sub-module 41 allows the monitoring and estimation device 1 to be configured as a function of the detected failure cases, thus ensuring never supplying said monitoring and estimation device 1 with a measurement of a sensor C1, C2, ... CN with a fault.
The variance determined depends on the sensor C1, C2, ... CN and accounts for its accuracy. In the event of a sensor failure C1, C2, ... CN, the variance of the sensor measurement C1, C2, ... CN presenting a fault is significantly increased so that it no longer has an impact in the estimation module. As regards the booleans of validity, their value is modified in the event of failure and in the event of revalidation. Only the use of estimation modules based on probability densities requires the association of variances with each of the measurements. In other cases, the validity booleans will be used so as not to update the monitoring and estimation process with erroneous measurements.
The adaptation sub-module 41 also ensures the observability of the system. Consequently, in the event of a C1, C2, ... CN sensor failure, it acts on the adjustment of the estimation module in order to freeze certain states to ensure the convergence of the estimation module. This procedure can be set off-line by a user depending on the failure cases that may be encountered.
Finally, the adaptation sub-module 41 also makes it possible to correct the current mass as a function of an estimate of a mass error obtained on the previous iteration or initialized by the initialization module 3 and of an associated status. the parameter corresponding to the mass.
The estimation sub-module 42 is configured to determine the estimate of the values of the parameters relating to the flight as well as an estimate of the error of said mass, on the basis of: measurements of the parameters relating to the flight provided by said sensors C1, C2, ... CN, - parameters relating to the flight estimated at the previous iteration or initialized by the initialization module 3 and - the variance and / or the boolean validity of each of the measurements of the parameters relating to the flight and adjustment parameters determined by the adaptation sub-module 41.
The estimation sub-module 42 is also configured to determine the innovations associated with each of the flight-related parameters. An innovation is equal to the difference between a measurement of a flight-related parameter and an estimate value of said flight-related parameter. Finally, it is configured to generate the residuals from the terms of innovation and relative parameters measured and estimated flight.
The detection module 5 can include the following sub-modules: a detection sub-module COMP31 51; and - a COMP32 52 validation sub-module.
The detection sub-module 51 is configured to determine: - the common status associated with the sensor C1 configured to measure the angle of incidence a of the aircraft AC and with the parameter P1 corresponding to the current mass and - the status associated with the other sensors C2, C3, ..., CN.
These statuses are determined from: o measurements of the parameters relating to the flight supplied by said sensors C1, C2, ..., CN, o the estimation of the values of the parameters relating to the flight as well as the mass error, o statuses associated with each of said sensors C1, C2, ..., CN and with a parameter P1 corresponding to the current mass of the aircraft AC determined in the previous iteration or initialized by the initialization module 3, o residues.
The incidence angle and current mass validation sub-module 52 is configured to determine the status associated with the parameter P1 corresponding to the current mass and the status associated with the sensor C1 configured to measure the angle of incidence at.
The determination is made from: - the common status associated with the sensors C1 configured to measure the angle of incidence of the aircraft AC and the parameter P1 corresponding to the current mass, - the statuses associated with the other sensors (C2, C3 , ..., CN), - estimated flight parameters, - estimated mass error, - measured flight parameters, - residuals generated by the estimation sub-module 42, and - d 'a lift coefficient CL provided by on-board modeling and supplied by the parameters relating to the flight measured by the sensors C1, C2, ..., CN and by the parameters relating to the estimated flight.
In the following description, the index m refers to the measurements from the sensors of the aircraft used at the input of the estimation sub-module 42.
According to a first embodiment, the estimation sub-module 42 corresponds to a Bayesian estimation module of extended Kalman filter type associated with the following system: f X (t) = / F (X (t)) (Y (t) = g (x (t), z (t), cL (x (t), z (t))) 'in which X is the state vector, Y is the observation vector, Z is an auxiliary measurement vector, T is the function associated with the equation of state and g is the function associated with the equation of observation.
The auxiliary measures vector Z presents as expression: Z = (ÏHmAi '5sPi, ψ, φ, θ, ην ,, m, conf, Vg, V „, V„, zg), V m 4ijn Λ1τη Kxom Ky ° m ° z ° m in which: - iHm corresponds to a deflection measurement of the horizontal plane, - ôqi ^ corresponds to a deflection measurement of aircraft elevators (AC), - ôspi ^ corresponds to a deflection measurement of spoilers of the aircraft (AC), - ψ corresponds to a heading measurement, - φ corresponds to a tilt angle measurement, - θ corresponds to a tilt measurement, - nx corresponds to a measurement of the longitudinal load factor in the coordinate system linked to the aircraft (AC), - m corresponds to the current mass parameter of the aircraft (AC), - conf corresponds to a measurement of configuration of the aircraft (AC), - V „, Ve, V „correspond to the measurements of the components of
gx ° m gy ° m gz ° m K ground speed in the terrestrial coordinate system, and - zg ^ corresponds to a measurement of geometric altitude.
The configuration measurement corresponds, for example, to the position of the spout and the flaps of the aircraft AC.
The Kalman filter is associated with the state vector X and the observation vector Y.
The Kalman filter does not consider the classic AC aircraft states but considers the atmospheric states as well as biases.
The state vector X presents as expression:
in which: - (WXo, Wyo, WZo) correspond to the three components of the wind speed in the terrestrial coordinate system, - AISA corresponds to a difference in temperature between a current static temperature and a temperature determined from a model of standard atmosphere at a current geometric altitude, - bCt corresponds to a modeling bias of the lift coefficient, and - Cbx corresponds to a barometric correction term.
The derivative of the state vector X presents as expression:
in which, xb corresponds to a characteristic time associated with the Markov process used to characterize the evolution of the modeling bias. Without limitation, this characteristic time is fixed at a few seconds, for example 30 seconds. Similar modeling can be used to describe the evolution of the wind components.
The observation vector Y presenting as expression:
in which: - am corresponds to an angle of incidence measurement, - pm corresponds to a skid measurement, - PSm corresponds to a static pressure measurement, - nz corresponds to a measurement of vertical load factor in a linked frame of reference at the aircraft, - PTm corresponds to a total pressure measurement, and - TTm corresponds to a total temperature measurement. The incidence has the expression:
in which u and w are, respectively, the longitudinal and vertical components of an air speed having as standard where v is the lateral component.
The components of air speed V have the expression:
cos θ cos ψ cos θ sin ψ sinS sincpsinOcosil / - coscpsinil / sin φ sin θ sinil / + cos φ cosi | / - sin φ cos θ _cos φ sin θ cos ψ + sin φ sin ψ cos φ sin θ cosi | / + sin φ sinil / - cos φ cos Θ.
in which: - Vgxo, Vgyo, Vgzo are the components of the ground speed in the terrestrial frame of reference, - Ψ corresponds to a course measurement, - φ corresponds to a measurement of angle of heel, and - θ corresponds to a measurement d tilt.
The slip has the expression:
The static pressure has the expression: PSm = ^ (ZPjn) ’in which ζ is a function connecting the measurement of the pressure altitude zPm to the static pressure PSm according to the formula:
in which zPii = 11 km corresponds to the standard altitude of the tropopause, Pu = 226,321 mbar and Tu = 216.65 k correspond to the standard static pressure and static temperature at the tropopause, GTzo = 0.0065 k / m le standard temperature gradient for zPm <zPll, g at the acceleration of gravity and r the specific air constant. Pressure altitude has the expression:
in which T15 = 288.15 K.
The vertical load factor nZi ^ has the expression:
tan α, in which γ is the adiabatic index of air (equal to 1.4), S is the reference surface of the aircraft, M is the Mach number, CL is the coefficient of lift, nXim is the horizontal load factor, m is the mass of the aircraft, g is the acceleration of gravity. The Mach number M has the expression M = j =, in which in which Ts is the static temperature and r is the specific air constant.
The static temperature Ts has the expression Ts = To + GTzozg + AISA, in which To = 273.15 K, GTzo = 0.0065 K / m and zG is the geographical altitude.
Pressure
total has the expression:
The total temperature has the expression:
The sensors considered are therefore three anemometric sensors (static pressure, total pressure and total temperature sensors), angle of attack probes C1, positioning sensors such as satellite geolocation systems (GPS for " Global Positioning System "in English) and inertial units such as 1RS systems (1RS for" Inertial Reference System "in English). A first anemometric sensor measures the total pressure. A second anemometric sensor measures the static pressure. A third anemometric sensor measures the total temperature.
Among the parameters that can be erroneous, there is the parameter P1 corresponding to the mass of the aircraft AC. The parameter P1 is equal to the sum of the mass of the aircraft AC without fuel and the mass of the
fuel. This parameter P1 may be erroneous on takeoff from aircraft AC until the end of the flight.
The adjustment of the extended Kalman filter is carried out by means of covariance matrices of state and measurement noises and on initialization implemented by the initialization module 3 on a state vector Xo and a matrix of covariance of the error Po. From an algorithmic point of view, an analytical formulation is preferably used for the calculation of the Jacobian matrices associated with the Kalman filter.
Preferably, during a correction step of the Kalman filter, a sequential processing algorithm of the measurements is used in order to be able to select valid measurements on a case-by-case basis, without modifying the settings of the covariance matrix of the noise of measurements R This notably makes it possible to avoid a matrix inversion operation which is more demanding in terms of computation time. For the determination of the valid measurements, the validity vector f = [FIsensors] will be used obtained from the combinations of the various fault indicators defined in the detection sub-module 51 whose value refers to the validity of the sensors C1, C2, ..., CN used as input and of parameter P1 corresponding to the ground. This vector refers to the value of variances and booleans of validity. The passage of the value of a boolean of validity from 1 to 0 or a drastic increase in the associated variance makes it possible to no longer take into account the invalid sensor when updating the states while the passage of a boolean of validity from 0 to 1 or reselection of a standard variance once again allows the valid parameter and / or sensor to be selected. This is called an adaptive extended Kalman filter for the entire estimation module. The validity vector f is kept up to date thanks to the detection module 5. The set of values of the parameters of the observation vector Y (t) and of the auxiliary measurement vector Z (t) define the inputs of the submodule d estimate implementing the extended Kalman filter. The extended Kalman filter is formed to deliver in real time, during a flight of the aircraft AC, estimates of the selected flight parameters and of the atmospheric and bias parameters, and in particular makes it possible to recalculate a calibrated speed estimated CAS according to the formula :
With Po = 101325 Pa, To = 273.15 K ety = 1.4, the adiabatic incidence of air and r = 287.058J.kg_1.K_1, the specific constant of air.
The estimation sub-module 42 generates the following residuals at an iteration k.
A first residue has the expression ^ (tjj = £ a (tk) +
in which £ a (tk) corresponds to the innovation term associated with the angle of incidence a at a time tk, bCt corresponds to the estimated modeling bias of the lift coefficient, and CLa (conf (tk)) corresponds to a tabulated value of the coefficient of lift CLa depending only on the value of the parameter corresponding to the configuration of the aircraft AC (position of the nose and flaps of the aircraft AC) at a time tk,
A second residue r2 has the expression at time tk r2 (tk) =
in which: - γ corresponds to the adiabatic coefficient of air, - TTm corresponds to the measured flight parameter of total temperature, - PTm corresponds to the total measured pressure, - zPm corresponds to the measured pressure altitude,
- ζ corresponds to the function linking the measurement of the pressure altitude to the static pressure, and - Ts (zPm, tk) corresponds to an estimate of the static temperature. The estimate of the static temperature Ts (zPm, tk) is recalculated from the parameters estimated at the current time tk and previous time tk_! depending on the value of the residue r1; according to the formula:
Ts (zpm <tk) = T15 + GTzo (zPm (tk) + £ (s) [cbx (tk) nr ± (r1 (tk)) + Cbx (tk_!) (L - n ^ Crrttk))))) + £ (s) [âîSÀCtkjn ^ Crtttk)) + AÏSÀ (tk-i) (l - ΠΓ ± (Γι (ΐ0))), in which £ is the transfer function of a low-pass filter and n + (r ) = H (r + y) - H (r - y) where H is the function of Heaviside, and rf corresponds to the limits associated with the residue defined in the following description.
A third residue r3 has the expression at time tk, r3 (tk) =
in which: - m corresponds to the current mass of the aircraft AC, - S corresponds to the reference surface of the aircraft AC, - g corresponds to the acceleration of gravity, - γ corresponds to the adiabatic coefficient of air , - nz corresponds to the measured vertical load factor, - nx corresponds to the measured longitudinal load factor, - corresponds to the measured angle of incidence, - zPm corresponds to the measured pressure altitude, - TTm corresponds to the total measured temperature , - ζ corresponds to the function connecting the measurement of the pressure altitude to the static pressure, - Ts (zPm, tk) corresponds to the estimate of the static temperature defined in the residue r2, and
- Cz corresponds to the lift coefficient calculated from the estimated flight parameters.
Without limitation, the first residue r4 is filtered over a time τΓ [. a few seconds, while the residues r2 and r3 are forced to a zero value as long as the geometric altitude zG of the aircraft AC is less than a limit altitude chosen in a nonlimiting manner at 7000 feet (approximately 2133.6 m) because of the inaccuracies of the expression expressing the pressure altitude
below 7000 feet.
For example, the time τΓ [. is equal to 10 s.
For the determination of the status of the sensors C1, C2, ... CN and of the parameter P1 corresponding to the current mass of the aircraft AC, the detection sub-module 51 is configured to: - assign to each residue η a maximum limit η + and a minimum limit rf with i between 1 and 3; - build two validity indicators in the form of boolean VPs and VPt associated with the static pressure and total pressure sensors from the estimated parameters and measurements from the aircraft sensors; - deduce therefrom residue indicators Rj associated with each residue η and validity indicators V; ; - identify the appearance of a fault when the sum of the residual indicators is strictly greater than zero (£ Rj> 0) and identify (or isolate), in the event of a fault, the faulty sensor by comparing the current values of the indicators of residue to those listed in a table identified offline or online listing the cases of failure according to the different combinations of values of the residue indicators Rj.
The validity indicators VPs and VPt are constructed as follows.
The validity indicator VPs is worth 1 if the relation | £ h (s) (zPm -zGm) | <lPs is checked. VPs is 0 if said relationship is not verified.
The term lPs corresponds to a limit determined experimentally as a function of the dynamics of the aircraft. The term £ h corresponds to a transfer function of a high-pass filter with a time constant chosen without limitation to a few seconds, for example 30 s. The validity indicator VPt is worth 1 if the residue crosses its respective limits, at an instant tk, and if 3n e M such that tn e [tk -xPT, tk] satisfying | (1 - · £ τ) (μΡτ (ϊπ ) - MPt (tn_j)) | <1Ρτ, with: - τΡτ corresponding to a constant chosen without limitation to 120 seconds, - corresponding to a transfer function of a low-pass filter having as time constant τ chosen without limitation to a few hundred seconds, for example 700 s, - I M corresponding to a constant chosen in a nonlimiting manner equal to 8, and - 1Pt corresponding to a limit determined experimentally as a function of the dynamics of the aircraft.
To derive a residue indicator R; associated with a residue η, we refer to the value of the residue η. If the value of the residue η is respectively greater or less than the maximum limit η + or the minimum limit rf, the residue indicator R; is equal to 1, otherwise the residue indicator R; is zero. In the case of a residue indicator R; associated with a validity indicator Vj, the residue indicator R; is equal to the validity indicator Vj.
Each column of the table, listing the failure cases according to the different combinations of value of the residue indicators R;, corresponds to a fault index FI; (“Fault indicator” in English) and is the combination of residue indicators R1 (R2 -Rm can take the value 0 or 1 and each line corresponds to the values of a residue indicator Rj for each of the fault indices FIlP FI2p FIm constructed A fault index Flj refers to the status of the sensor Ci, with the exception initially of the sensor measuring the angle of incidence C1 for which the fault index FIa / m refers to a common status of the measurement of the angle of incidence measured by a sensor for measuring the angle of incidence C1 and of the parameter P1 of the current mass of the aircraft.
The maximum limit η + and the minimum limit rf are determined from thresholds rp, tabulated according to estimated flight parameters, centered on a value of central residue rim which corresponds to the residue η filtered for a time τ, which depends on each residue. Thus, the maximum limit η + has the expression η + = rim + rp and the minimum limit rf has the expression rf = rim -rr-
There are many ways to define rp thresholds. Preferably, the threshold is chosen to be symmetrical around a filtered value, denoted rim, of the raw residue over a sufficiently long time τΓ. The distance Ιη1 - rim | can depend on the precision of a modeling and the precision of sensors C1, C2, ... CN. In the chosen application case, it can be a function of the Mach, of the configuration of the aircraft AC, of the deflections control surfaces but also of the diagonal elements of the covariance matrix of the error calculated via the previously adaptive extended Kalman filter. describes:
in which, Uj is a dependence vector making it possible to relate the influence of each state to measure i.
In order to avoid re-boarding of thresholds in the event of a breakdown, it is recommended to introduce saturators to force η + and rf to maintain themselves within a realistic predefined interval:
The threshold rf for the first residue ιγ is defined according to the confidence which one carries in the model of the coefficient of lift CL. It may for example depend on the configuration of the aircraft AC, the Mach number, the position of the landing gear of the aircraft AC (retracted or extended), the position of the control surfaces whose effects have not been taken into account in the modeling and accuracy of the incidence probes. Without limitation, the filtering time τ £ is chosen to be 500 seconds.
The thresholds for the second residue r2 and the third residue r3 are defined according to a different logic since they are associated with Mach measurement deviations. Their value can depend on the accuracy of the airspeed sensors and on the estimated or measured flight parameters such as the geometric altitude zG.
For the isolation of a fault, the algorithm of the detection submodule 51 refers to the combinations of the fault table below. The acronym FI refers to the fault indicator while the index f = 0 refers to the nominal case (that is to say in the absence of failure before the detection of the fault) and f> 0 in the case of degraded operation (the measurement of at least one parameter has already been detected as at fault and is therefore no longer used by the system). Rvl and Rv2 are associated respectively with the validity indicators VPs and VpT. FIa / m, f = o FIpTf = 0 FIPsf = 0 FITt f = 0 R ^ î î Ô / ï (0/1) R2 0/1 0/1 0/1 1 R3 0 0/1 0/1 1
Rvl 0 0 1 0
rv2 Ο 1 ο ο
These combinations depend on the setting of the estimator and more particularly on the precision of the sensors C1, C2, CN used. They are determined offline or online via a dedicated algorithm. The notation ‘0/1’ refers to the values of the residual indicators having no impact on fault isolation, the isolation being satisfied via the other dependencies.
According to the combination of 1 and 0 obtained on the different FI fault indicators, it can be deduced whether there is a fault and its origin.
For example, the status of the total pressure sensor PT corresponds to a failure when Ri and RV2 are equal to 1. The common status of the angle of attack sensor a and of the mass m corresponds to a failure state if Ri equal to 1 and R3, Rvi and RV2 equal to zero.
The faulty sensor sub-module 51 of sensor C1, C2, ..., CN allows both the detection and the isolation of the fault, with an indeterminacy to be raised between a fault on the angle of attack measurement a and on the current mass m, translated by the notation α / m in FIa / mf = 0 which refers to both FIaf = 0 and FImf = 0 since they have the same signature and are therefore confused. The validation sub-module 52 makes it possible to remove the ambiguity.
In the case where a first fault has already been detected (f> 0), the fault indicators for valid sensors (with which the fault indices Rj are associated) can be reduced to a simple indicator:
Failure detection will then be possible while source identification cannot be carried out directly without the addition of external information to the system presented. The abrupt breakdowns remain all the same
detectable and isolable via the use of the previous dependence matrix by considering only the sensors C1, C2, CN, the residues ri, r2, r3 and the validity indicators VPs, VPt still valid.
These indicators are then communicated to the validation sub-module 52 with the current value of the mass m as well as the estimation of the modeling bias of the lift coefficient bCL, the lift coefficient CL and the first residue
The validation sub-module 52 makes it possible to distinguish a fault on the incidence sensors C1 from a mass error. This validation sub-module 52 nevertheless requires a minimum variation of the angle of incidence a to operate. An indicator which will be called "dynamic indicator" is therefore established there in order to validate the results obtained. As soon as the detection sub-module returns a fault on the incidence a or the mass m, the maximum difference in variation of mass m from the detection time L is calculated: From the estimation of the first residue r1; we calculate the following mass error m at each time t:
in which CL corresponds to the estimate of the lift coefficient, CLa (conf) to the coefficient CLa from a simplified model only depending on the configuration of the aircraft AC and m the current mass of the aircraft AC.
We define the dynamic indicator on the value of the incidence a. Since the measurement of this can be wrong, we construct a virtual incidence av from the raw measurement of the estimated modeling bias am and the residue associated with the incidence rCa:
In this way, the virtual incidence av will compensate for any failure on the measured incidence. The latter will nevertheless remain affected by a mass error m which will introduce a bias but its variation Δαν will be identical to that of the actual incidence.
A first variant for the definition of virtual incidence corresponds to the integration of the following formula:
in which: og is the acceleration of gravity, oq corresponds to the angular speed of pitching, o nZi corresponds to the measurement of the vertical load factor expressed in the reference linked to the aircraft AC, ο V corresponds to the estimate of air speed.
The auxiliary measurement vector Z is then increased by measurement q corresponding to the measurement of angular velocity in pitch in the reference frame of the aircraft.
The variation of the virtual incidence Δαν has the expression:
We then define a minimum variation threshold to be reached by the virtual incidence Δαν since the detection of the failure in order to allow the isolation of the failure between an error of measurement of angle of incidence a and an erroneous current mass m , and in the second case, the evaluation of the associated mass error via a second calculation. We then define t2 such that:
A second threshold on the variation in estimated mass makes it possible to deduce therefrom if it is large enough to be associated with a fault of the angle of attack sensor C1. This threshold depends for example on the quality of the modeling used for the lift coefficient CL.
We deduce the maximum difference in mass variation A2m from the moment of detection until time t2:
We define A2mlim the maximum variation limit allowing to deduce if the failure can be identified as a defect in the angle of attack sensors C1 or as a current mass error m: siA2m <A2mlim then FIa, f = o = θ FIm, f = o = 1 otherwise FIa, f = o = 1 FIm, f = o = θ
The validation sub-module 52 finally makes it possible to establish the fault indicators associated with the incidence FIaf = 0 and with the mass FImf = 0. There is nevertheless a type of failure on the incidence a which can lead to a bad interpretation: faerr (t) = a (t) + Aa (t) t Aa (t) = K (a (t) - a0) II s 'is a scale factor fault on the incidence a. All other types of faults are correctly identified. In order to minimize this type of error, two additional checks are possible. First, verify that the estimated mass is in the range between the minimum and maximum take-off mass defined for the AC aircraft. Then a
request for verification of the weight entered on take-off to the pilot is possible, as is the case in certain situations.
In a first alternative embodiment, it is possible to integrate the motor measurements and considerably increase the observability of the system and therefore the detection capabilities of the algorithm via the addition of a modeling called engine-nacelle modeling described below. before. To do this, we integrate three new observations: - the total virtual pressure from the engine-nacelle model PTeng, - the virtual static pressure from the engine-nacelle model Ps, ^ eng ’- the total engine temperature TT. 1 Aeng
These two virtual measurements come from engine-nacelle modeling using only the engine static pressure Pmot and the static pressure measured in the nacelle Pnac and the total engine temperature TTeng. They have two common failure modes since a failure of one of the two static pressures causes a fault in the virtual static pressure and the virtual total pressure and a failure in the total engine temperature results in a fault in the latter. ci and two virtual measurements.
Thus, the observation vector presents as expression:
in which - ρτΡησ corresponds to a value of total pressure resulting from the eng nacelle-engine modeling, - Ps „„ „corresponds to a value of static pressure resulting from the cng modeling, and - TT a measured value of total temperature resulting from the measurement of 1 engm r total engine temperature.
When adjusting the Kalman filter, we will choose not to use the motor measurements to update the estimated states. They will be used only for detection and will then replace the missing measurements after certain cases of failure. The variance specified for each other sensor is otherwise used for filter adjustment.
The sensors C1, C2, ..., CN considered are those of the first variant to which is added the total engine temperature sensor Tr σ and the cng
virtual static pressure sensors PSpntJ, and total engine pressure eng
Pt ‘eng
The residues generated are as follows: - a fourth residue r4 having the expression r4 (tk) = εΡ (tk) in eng where εΡ (tk) corresponds to the difference at a time (tk) between the measured eng value of the total pressure and said virtual measurement resulting from the engine-nacelle PT modeling. eng - a fifth residue r5 having for expression r5 (tk) = εΡδ (tk) in seng which εΡδ (tk) corresponds to the difference at a time (tk) between the measured eng value of static pressure and said virtual measurement resulting from the modeling Pc, and ^ eng '- a sixth residue r6 having for expression r6 (tk) = εΤτ (tk) in eng where εΤτ (tk) corresponds to the difference at a time (tk) between the measured eng value of total temperature and said TT motor measurement. eng
Without limitation, the residues η generated during the estimation sub-step can also be filtered over a time Trc.
The thresholds r ^, rf and rf associated respectively with the residues r4, r5 and r6 to determine the maximum limit and the minimum limit depend on the accuracy of the model associated with the virtual engine sensors and the accuracy of the static engine pressures Peng, nacelle Pnac and of the total temperature sensor that feed it.
For the detection of a fault, the algorithm of the sub-detection module 51 then refers to the fault indices defined according to the combinations of the fault table below. FI «/ m, f = o FIpTf = 0 FIPsf = 0 FITt f = 0 FIPengf = 0 FITt f = 0 î î Ô / ï (0/1) Ô Ô R2 0/1 0/1 0/11 ο ο R3 ο 0/1 0/11 ο ο R4 Ο 0 10 10/1 R5 Ο 10 0 10/1 R6 Ο 0 0 1 Ο 1 RV1 Ο 0 0/10 Ο Ο
Rv2 0 0/1 0 0 ο ο
This first variant has the advantage of a large number of observations. Consequently, it is possible to isolate the source of a failure much more quickly than previously by means of the indicators marked by the notation ‘T. Conversely, although the notation ‘0/1’ indicates a possible exceeding of the associated threshold, it is not necessary to be identified to quickly isolate the fault, the isolation being satisfied via the other dependencies. These combinations depend on the setting of the estimator and more particularly on the precision of the sensors C1, C2, ..., CN used, as evidenced by the notation '(0/1)' which accounts for a possible overshoot depending of the chosen setting. They are determined offline by use or online via a dedicated algorithm.
Once a first fault has been detected and isolated, it is possible to continue monitoring using the residuals that are still relevant. For example, in the event of failure of the measurements from the engine model, we will be reduced to the formulation of the standard embodiment. It is therefore possible to detect and isolate at least two successive sensor failures and to reconstruct the missing parameters. Beyond this, the level of observability may no longer be sufficient and certain states may be frozen to continue to ensure the stability of the filter. Failure detection may still be ensured in certain cases.
In a second variant, it is possible to integrate in particular a kinematic model allowing monitoring and estimation of the soil parameters including the biases of the accelerometers bn, bn, bn on the three axes of the aircraft. This second variant is of interest because airspace is today experiencing some difficulties with GPS signals, especially when flying over territory using GPS jammers as is the case in certain countries at war. In this case, GPS measurements may no longer be available. In order to avoid an unplanned carryover of the detector estimator filter, it is necessary to make sure to detect a carryover of the GPS measurements in order to allow the inertial sensors to hold their hands while they are unavailable. The estimation of accelerometric biases allows to refine the estimation of soil parameters in the absence of GPS measurements
In this second variant, the state vector X has the expression:
in which: - Vgxo - vgyo Λζο correspond to the three components of the ground speed in the terrestrial coordinate system, - bn, bn, bn correspond to the three components of accelerometer bias in the coordinate system linked to the aircraft AC, - zG corresponds to a geometric altitude.
The derivative of the state vector present as expression:
in which
Mrot = (cosθcosψ sin φ sin θ cos ψ - cos φ sin ψ cos φ sin θ οο5ψ + sin φ 5ίηψ cos θ sin ψ sin φ sin θ sin ψ + cos φ cos ψ cos φ sin θ 5ίηψ - sin φ cos ψ . sin θ - sin φ cos0 - cos φ cos θ /
The auxiliary measurement vector Z is increased by the measurement nyim corresponding to the measurement of the lateral load factor in the reference frame of the aircraft.
The observation vector Y therefore has the expression:
in which: - Vgxo ’Vgyo> vgXo corresponds to measurements of the three components of ground speed, and - zGm corresponds to a measurement of geometric altitude.
This second variant can be coupled or not with the first variant for a more complete formulation and therefore more performance. This nevertheless has the disadvantage of being more complex and therefore of presenting a much higher computational move as well as a more delicate adjustment of the estimator filter.
Knowledge of the kinematic model makes it possible to monitor GPS measurements by studying the residues associated with the new states introduced and the evolution of the accelerometric biases bn, bn, bn. In nominal operation, this is done at low frequency and with a low amplitude. Conversely, any failure of GPS measurements leads to abrupt changes of large amplitude.
According to a third variant, the lateral component of the air speed v is assumed to be zero, which amounts to considering the sideslip β zero. this is
true most of the time. Certain situations such as engine failure can undermine this assumption. However, the wander values remain relatively low in all cases and even in the event of large variations in the wander angle, this has very little impact on the estimation and detection process and its performance. This assumption therefore introduces very few errors while it eliminates all monitoring on the skid probes (which would otherwise have required establishing a lateral model of the aircraft AC). Coupling with the previous variants described is possible.
According to a second embodiment (Figure 1), the statuses associated with some of said sensors C1, C2, ... CN are also determined from auxiliary statuses associated with these said sensors capable of being sent to the detection module by a module COMP4 9 monitoring system. The detection sub-module 51 then takes care of translating the statuses sent by the external monitoring module 9 before transmitting the translated statuses to the estimation module 4. This second embodiment can be combined with the other embodiments.
According to a third embodiment shown in FIG. 4, in the case where the aircraft AC uses hardware redundancy, the inputs of the estimation module 4 initially correspond to the consolidated measurements as they come from the output of a module 11 based on a majority vote. One can however imagine cases where the consolidated measurement is invalidated by the voting module 11 and is therefore at fault, but that one of the sensors of the corresponding type is still valid, which may be the case with certain common modes of breakdown. In this case, it is interesting to have the ability to retrieve the measurement still valid. FIG. 4 represents several sets of redundant sensors C1, C2, C3, C4, C5, C6 comprising one or more sensors. For example, the set of sensors C1 comprises sensors C1a, C1b, C1c of angle of incidence. The sensor set C2 includes static pressure sensors C2a, C2b, C2c. The C3 sensor set includes C3a, C3b, C3c total pressure sensors. The C4 sensor set includes C4a, C4b, C4c total temperature sensors. The sensor set C5 includes sensors C5a and C5b respectively corresponding to a set of satellite geolocation systems and a set of inertial units. The set of sensors C6 corresponds to virtual sensors of virtual total pressure PTeng, of virtual static pressure Ps originating from the engine-nacelle modeling and of r ~ i '-‘eng the total engine temperature Tr σ
The monitoring and estimation device 1 comprises a unit verification module COMP5 10. When a fault is detected for a measurement used at the input of the estimation module, the unit verification module is configured to: - reconfigure the sub- estimation module 42 so as not to take into account the measurement at fault, - after a convergence time tcv, calculate the differences between the estimates of said parameters relating to the flight and each of the measurements originating from the plurality of sensors. For each of the measurements from the plurality of sensors, if the absolute value of the difference is less than a predetermined value, the corresponding measurement is used for the estimation sub-module 42.
One possible variant concerns the use of methods similar to the extended Kalman filter, using the same set of equations as the integration of an unscented Kalman filter, of particulate filters, or any similar variant using their respective procedures and the equations given above.
The monitoring and estimation device 1 of parameters relating to the flight of an aircraft AC as described above, implements a method (FIG. 2) comprising: - an initialization step E1, implemented by the initialization module 3, consisting in initializing the statuses of sensors C1, C2, CN configured to determine the flight parameters of the aircraft AC and of a parameter P1 corresponding to the mass of said aircraft AC and in initializing parameters used during the implementation of the monitoring and estimation process 1.
The method further comprises the following steps, implemented iteratively: - an estimation step E2, implemented by the estimation module 4, consisting in determining an estimate of the values of the parameters relating to the flight of the aircraft AC as well as an estimate of the error of said mass, from: o measurements of the parameters relating to the flight provided by the sensors C1, C2, ... CN, o parameters relating to the flight initialized in the step initialization or estimated at the previous iteration of the estimation step E2 and o of the statuses associated with each of said sensors C1, C2, ..., CN, the estimation step E2 also consisting in generating residues η which are a function of the values of the flight parameters measured and estimated and of innovation terms which correspond to the difference between a measured flight parameter value and said estimated value; a first transmission step E3, implemented by the first transmission module 7, consisting of: o transmitting to a user device 6 and to the detection module 5 a signal representative of the estimation of the values of the parameters relating to the flight of the aircraft AC as well as the mass error, determined in the estimation step E2, o to send a signal representative of the residues generated in the estimation step E2 to said detection module 5; a detection step E4, implemented by the detection module 5, consisting in determining the different statuses associated with each of said sensors C1, C2, ..., CN and with a parameter P1 corresponding to a current aircraft mass AC, from: o said residues determined in the estimation step, o the estimation of the values of the parameters relating to the flight as well as the estimated mass error, determined in the estimation step E2, o said statuses determined in the previous iteration or initialized in the initialization step; a second transmission step E5, implemented by the second transmission module 8, consisting in transmitting to the user device 6 and, on the next iteration, to the estimation module 4 the different statuses associated with each of said sensors C1, C2, ..., CN and the status associated with said parameter P1 corresponding to the current mass.
In addition, the estimation step E2 comprises the following sub-steps: - an adaptation sub-step E21, implemented by the adaptation sub-module 41, consisting in determining a variance and / or a boolean of validity associated with each of the measurements of the parameters relating to the flight provided by the sensors C1, C2, ..., CN as well as of the adjustment parameters associated with the estimation algorithm used in the estimation sub-step E22, from: o said measurements of the parameters relating to the flight and o from the statuses associated with each of said sensors C1, C2, ..., CN; the adaptation sub-step E21 also consisting in correcting the current mass from a mass error estimated at the previous iteration or initialized at the initialization step E1, and from a status associated with the parameter corresponding to the mass, an estimation sub-step E22, implemented by the estimation sub-module 42, consisting in determining the estimate of the values of the parameters relating to the flight as well as an estimate of the error of said mass from: o measurements of the parameters relating to the flight provided by said sensors C1, C2, ..., CN, o parameters relating to the flight estimated at the previous iteration or initialized in step E1 of initialization and o from the variance and / or the boolean validity of each of the measurements of the flight-related parameters and of the adjustment parameters determined in the adaptation sub-step E21, the estimation sub-step E22 also consisting of g list the residuals based on the estimated and measured flight parameters and innovation terms.
In addition, the detection step E4 comprises the following sub-steps: a sub-step E41 for detecting a faulty sensor and erroneous flight parameters, implemented by a detection sub-module 51, consisting in determining : o the common status associated with the sensor C1 configured to measure the angle of incidence a of the aircraft AC and with the parameter P1 corresponding to the current mass and o the status associated with the other sensors (C2, C3, ..., CN), from: o measurements of the parameters relating to the flight supplied by said sensors C1, C2, ..., CN, o from the estimation of the values of the parameters relating to the flight, o the statuses associated with each of said sensors C1 , C2, ..., CN and a parameter P1 corresponding to a current mass of the aircraft (AC) determined in the previous iteration or initialized in the initialization step E1, and o of the residues; a sub-step E42 of validation of the angle of incidence and of the current mass, implemented by a validation sub-module 52, consisting in determining the status associated with the parameter P1 corresponding to the current mass and the status associated with the sensor C1 configured to measure the angle of incidence a, from: o the common status associated with the sensor C1 configured to measure the angle of incidence a of the aircraft AC and with the parameter P1 corresponding to the current mass , o statuses associated with the other sensors C2, C3, ..., CN, o parameters relating to the estimated flight, o the estimated mass error, o parameters relating to the measured flight, o residues generated in the sub step E22 of estimation and o of a lift coefficient CL provided from an on-board modeling supplied by the parameters relating to the flight estimated and measured by the sensors C1, C2, CN.
The determination of the status of the sensors C2, ..., CN and of the common status associated with the status of the sensor C1 and with the parameter P1 corresponding to the mass, during the substep E41 for detecting a faulty sensor comprises the following substeps : - a sub-step E411 of allocation to each residue of a maximum limit η + and a minimum limit η-, of construction of validity indicators V; then residue indicators Rj associated with each residue η and validity indicator V ;; - a sub-step E412 for identifying faults (Σ Rj> 0) and isolating its source by identifying the combination of the current values of the residue indicators Rj with those listed in a pre-identified table offline in a preferred embodiment, listing the failure case as a function of the different combinations of value of the residue indicators Rj. Each column of the table corresponding to a fault index FI; and is the combination of residue indicators R1 (R2 -Rm can take the value 0 or 1 and each line corresponds to the values of a residue indicator Rj for each of the fault indices FL, FI2, ... FIm constructed. A fault index Flj refers to the status of the sensor Ci, with the exception initially of the sensor measuring the incidence C1 for which the fault index FIa / m refers to a common status of the measurement of the angle of incidence measured by a sensor for measuring the angle of incidence C1 and of the parameter P1 corresponding to the mass of the aircraft.
For a consolidated flight parameter therefore measured from a plurality of sensors (FIG. 3), the method comprises the following sub-steps implemented by a unit verification module 10, when a failure is detected for the measurement used at the input of the estimation sub-module 42 for said flight parameter: - a sub-step E61 of reconfiguration of the estimation sub-module 42 so as not to take into account the erroneous measurement previously used at the input of the sub-module d estimation 42, - a sub-step E62 for calculating the difference, after a convergence time xcvf, between the estimation of said flight parameter and of the measurement originating from the plurality of sensors, for each of the measurements originating from the plurality sensors, if the absolute value of the difference is less than a predetermined value, the measurement being retained for the estimation module 4.

权利要求:
Claims (14)
[1" id="c-fr-0001]
1. Monitoring and estimation process: - parameters relating to the flight of an aircraft (AC); - sensor statuses (C1, C2, CN), these statuses being representative of an operation of said sensors (C1, C2, ..., CN); and - a status of a parameter (P1) corresponding to the current mass of the aircraft (AC), this status being representative of the validity of said parameter, characterized in that it comprises the following steps: - a step (E1) initialization, implemented by an initialization module (3), consisting in initializing the statuses of sensors (C1, C2, ..., CN) configured to determine flight parameters of the aircraft ( AC) as well as the status of the parameter (P1) corresponding to the current mass of the aircraft (AC) and to initialize parameters used during the implementation of the monitoring and estimation device (1); the method further comprising the following steps, implemented iteratively: - an estimation step (E2), implemented by an estimation module (4), consisting in determining an estimate of the values of the parameters relating to the flight of the aircraft (AC) as well as an estimate of the error of said mass, from: o measurements of the parameters relating to the flight provided by the sensors (C1, C2, ..., CN), o parameters relating to the flight initialized in the initialization step (E1) or estimated at the previous iteration of the estimation step (E2) and o the statuses associated with each of said sensors (C1, C2, ..., CN), the estimation step (E2) also consisting in generating residues (η) which are functions of the values of the parameters relating to the flight measured and estimated and of innovation terms which correspond to the difference between a parameter value measured flight and said estimated value; - a first transmission step (E3), implemented by a first transmission module (7), consisting of: o transmitting to a user device (6) and to a detection module (5) a signal representative of the estimation of the parameters of the parameters relating to the flight of the aircraft (AC) as well as of the estimation of the error of the current mass parameter, determined in the estimation step (E2), o to be sent to said detection module (5) a signal representative of the residues generated in the estimation step (E2); a detection step (E4), implemented by a detection module (5), consisting in determining the different statuses associated with each of said sensors (C1, C2, ..., CN) and with the corresponding parameter (P1) to the current mass of the aircraft (AC), from: o the estimation of the residue values (η) determined in the estimation step (E2), o the estimation of the values of the parameters relating to the flight of the aircraft (AC) determined in the estimation step (E2), o measurements of the parameters relating to the flight provided by the sensors (C1, C2, ..., CN), o the estimation of the error of the parameter (P1) of current mass determined in the estimation step (E2), and o of the statuses determined in the previous iteration of the detection step (E4) or initialized in the step of initialization (E1); - a second transmission step (E5), implemented by a second transmission module (8), consisting in transmitting to the user device (6) and, on the next iteration, to the estimation module (4) the various status associated with each of said sensors (C1, C2, ..., CN) and the status associated with said parameter (P1) corresponding to the current mass.
[2" id="c-fr-0002]
2. Method according to claim 1, characterized in that the estimation step (E2) comprises the following substeps: - an adaptation substep (E21), implemented by a submodule of adaptation (41), consisting in determining a variance and / or a boolean of validity associated with each of the measurements of the parameters relating to the flight provided by the sensors (C1, C2, ..., CN) as well as adjustment parameters associated with the estimation algorithm used in a estimation sub-step (E22), from: o said measurements of the parameters relating to the flight and o from the statuses associated with each of said sensors (C1, C2, ..., CN); the adaptation sub-step (E21) also consisting in correcting the current mass on the basis of a mass error estimated at the previous iteration or initialized in the initialization step (E1), and of a status associated with the parameter (P1) corresponding to the mass, the estimation sub-step (E22), implemented by an estimation sub-module (42), consisting in determining the estimation of the values of the parameters relating to the flight as well as '' an estimate of the error of said mass, on the basis of: o measurements of the parameters relating to the flight provided by said sensors (C1, C2, ..., CN), o parameters relating to the flight estimated in the previous iteration or initialized in the initialization step (E1) and o from the variance and / or the boolean validity of each of the measurements of the flight-related parameters and of the adjustment parameters determined in the adaptation sub-step ( E21), the estimation sub-step (E22) consisted nt also generate the residuals from the estimated and measured flight parameters and innovation terms.
[3" id="c-fr-0003]
3. Method according to any one of claims 1 or 2, characterized in that the detection step (E4) comprises the following substeps: - a substep (E41) of detection of faulty sensor and of relative parameters erroneous flight, implemented by a detection sub-module (51), consisting in determining: o the common status associated with the sensor (C1) configured to measure the angle of incidence (a) of the aircraft (AC ) and to the parameter (P1) corresponding to the current mass and o the status associated with the other sensors (C2, C3, CN), from: o measurements of the parameters relating to the flight provided by said sensors (C1, CN), o the estimation of the values of the parameters relating to the flight as well as the mass error, o the statuses associated with each of said sensors (C1, CN) and with the parameter (P1) corresponding to a current aircraft mass (AC ) determined in the previous iteration or initialized in the initialization step ion (E1) and o of the residues (η); a sub-step (E42) of validation of the angle of incidence and of the current mass, implemented by a validation sub-module (52), consisting in determining the status associated with the parameter (P1) corresponding to the current mass and the status associated with the sensor (C1) configured to measure the angle of incidence (a), from: o the common status associated with the sensor (C1) configured to measure the angle of incidence (a) of the aircraft (AC) and of the parameter (P1) corresponding to the current mass, o of the statuses associated with the other sensors (C2, C3, ..., CN), o of the parameters relating to the estimated flight, o of the estimated mass error, o of the parameters relating to the flight measured, o of the residues generated in the estimation sub-step (E22) and o of a lift coefficient (CL) supplied from an on-board modeling supplied by the flight parameters estimated and measured by the sensors (C1, C2, CN).
[4" id="c-fr-0004]
4. Method according to any one of claims 1 to 3, characterized in that the estimation sub-step (E22) corresponds to an extended Kalman filter associated with a state vector (X), a vector of observation (Y) and an auxiliary measures vector (Z), the auxiliary measures vector (Z) having as expression: Z = 5qim '5spim' Ψπρ θην nXljn 'm- COnf' VgXo m> VgYo m> VgZo m> zgm ) 'in which: - iHm corresponds to a deflection measurement of the horizontal plane, - ôqi ^ corresponds to a deflection measurement of aircraft elevators (AC), - ôspi ^ corresponds to a deflection measurement of spoilers the aircraft (AC), - ψ ™ corresponds to a heading measurement, - <pm corresponds to a tilt angle measurement, - 0m corresponds to a tilt measurement, - nx corresponds to a load factor measurement longitudinal in the coordinate system linked to the aircraft (AC), - m corresponds to the current mass parameter of the aircraft (AC), - conf corresponds to a measurement of aerodynamic configuration of the aircraft (AC), - Vgxo ’Vgyo, Vgzo correspond to measurements of the ground speed components in the terrestrial frame of reference, and - zg ^ corresponds to a measurement of geometric altitude; the state vector (X) having as expression:

in which: - (WXo, Wyo, WZo) correspond to the three components of the wind speed in the terrestrial coordinate system, - AISA corresponds to a difference in temperature between a current static temperature and a temperature determined from a model of standard atmosphere at a current geometric altitude, - bCt corresponds to a modeling bias of the lift coefficient, and - Cbx corresponds to a barometric correction term; the derivative of the state vector (X) having as expression:

in which, xb corresponds to a characteristic time associated with a dynamic of the modeling bias of the lift coefficient bCL, the observation vector (Y) presenting as expression:



in which: - am corresponds to an incidence measurement, - corresponds to a skid measurement, - PSm corresponds to a static pressure measurement, - nz corresponds to a vertical load factor measurement in a reference linked to the aircraft , - PTm corresponds to a total pressure measurement, - TTm corresponds to a total temperature measurement, and - zp corresponds to the pressure altitude and is expressed according to the equation

with T15 = 288.15 K, - ζ corresponds to a function relating the measurement of the pressure altitude zp to the static pressure with the following expression:

in which: - zPii = 11 km corresponds to the standard altitude of the tropopause, - PX1 = 226.321mbar and TX1 = 216.65 K correspond to the static pressure and the static static temperature at the tropopause, - GTzo = 0.0065 K / m the standard temperature gradient for zPm <ZPll '



- g at the acceleration of gravity - R the specific air constant, - Ts corresponds to the statistical temperature parameter and is expressed according to the equation Ts = To + GTzozg + AISA, with To = 273.15 K and GT n = 0.0065 K / m, - V corresponds to the air speed flight parameter and is expressed according to the equation

, with each component of the air speed defined in the aircraft reference frame (u, v, w) expressed according to the following expression:

cos θ cos ψ cosOsinil / sinO Ax0 - = sincpsinOcosil; - coscpsinil / sincpsinOsinil / + cos φ cos ψ - sincpcosO Vgy ° - W _cos φ sin θ cos ψ + sin φ sin ψ coscpsinOcosil; + sincpsinil / - coscpcosOj y - VV L θζο - M corresponds to the flight parameter of the Mach number calculated according to the norm of the air speed V according to the equation M = - ^ = with r corresponding to the specific constant of l 'air, the estimation sub-step (E22) generating at an iteration k the following residues: - a first residue (rj having as expression at a time tk =

in which: ° £ "(tk) corresponds to the innovation term associated with the measurement of the angle of incidence a at time tk, where bCz corresponds to an estimation of the modeling bias of the lift coefficient Cz at time tk, and o CZa (conf (tk)) corresponds to a tabulated value of the lift coefficient depending on a value of an aircraft configuration parameter (AC) at time tk,



- a second residue (r2) having as expression at time tk r2 (tk) =

in which: ο γ corresponds to the adiabatic coefficient of air, o TTm corresponds to a total temperature measured by one of the sensors (C2, CN) used at the input of the estimation module (4), o PTm corresponds to a total pressure measured by one of the sensors (C2, CN) used at the input of the estimation module (4), where zPm corresponds to a pressure altitude measured by one of the sensors (C2, ..., CN) used at the input of the module estimate (4), ο ζ corresponds to the function linking the measurement of the pressure altitude to the static pressure and o Ts (zPm, tk) corresponds to an estimate of the static temperature calculated from flight parameters estimated at time tk at the current iteration and at a time tk_! to a previous iteration as a function of the first residue (rj according to the formula: Ts (zPm, tk) = T15 + GTzo (zPm (tk) + £ (s) [c ^ CtiJrÇiCr-tttiJ) + Cb / Vj (l - ΠΓ ± (r, (tk))))) + £ (s) [AÎSA (tk) nr ± (ri (tk)) + ÂWk-i ^ ln ^ Crrttk)))), where L is the transfer function a low pass filter

where H is the function of Heaviside, and corresponds to the limits associated with the residue defined in the following description;


- a third residue (r3) having as expression at time tk r3 (tk) =

in which: om corresponds to the mass of the aircraft (AC), o S corresponds to the reference surface of the aircraft (AC), og corresponds to the acceleration of gravity, o nZim corresponds to a load factor vertical, o nXlm corresponds to a longitudinal load factor, o C, corresponds to the estimated lift coefficient, obtained from the estimated and measured parameters relating to the flight and the configuration of the aircraft (AC).
[5" id="c-fr-0005]
5. Method according to claim 4, characterized in that the observation vector (Y) has as expression:

in which: - ρτ „„ σ corresponds to a total pressure value from an engine-nacelle modeling eng,


- Ρ5ρησ corresponds to a static pressure value from engine-nacelle modeling, and - TT a measured total temperature value from a 1 engm r r sensor total engine-nacelle temperature; the estimation sub-step (E22) further generating the following residues: - a fourth residue (r4) having the expression r4 (tk) = εΡ (tk) in which £ pTeng (tk) corresponds to the difference between the value of total pressure measured and said total pressure value resulting from the modeling at a time (tk), - a fifth residue (r5) having for expression r5 (tk) = εΡδ (tk) in which £ Pseng (tk) corresponds to the difference between the measured static pressure value and said static pressure value resulting from the modeling at a time (tk), and - a sixth residue (r6) having for expression r6 (tk) = εΨΑΨ (tk) in which STATeng (tk ) corresponds to the difference between the measured value of total temperature and said value of total temperature resulting from the engine-nacelle measurement at a time (tk).
[6" id="c-fr-0006]
6. Method according to any one of claims 4 or 5, characterized in that the estimation sub-step (E22) corresponds to an extended Kalman filter associated with a state vector (X) and a vector of observation (Y) and an auxiliary measure vector (Z), the auxiliary measure vector (Z) having as expression: Z = (iH, δη., δςη., ψ ™, Πγ, ηγ, Γη, εοηβνσ, V „ , V „, z„), V qim 'splra »Tm'Ym' m> Xim 'Ylm <>> gxOm' gyOm 'SzOm Sm /' in which nyim corresponds to a measurement of lateral load factor in the coordinate system linked to l aircraft, the state vector (X) having as expression:

in which: - vgxo'Vgyo'Vgzo correspond to the three components of ground speed in the terrestrial coordinate system, - bn, bn, bn correspond to the three components of accelerometer bias in the coordinate system linked to the aircraft (AC), - zG corresponds to a geometric altitude; the derivative of the state vector (X) having as expression:



in which: - Mrot corresponds to a usual rotation matrix from the terrestrial frame to the frame linked to the aircraft (AC) and has for expression Mrot = (cosθcosψ sinc |) sin0cos4i - cos (j> sin4i cos φ sin θ cosi | / + sin φ sinil / x cos θ sin ψ sin φ sin θ sin ψ + cos φ cos ψ cos φ sin θ sin ψ - sin φ cos ψ J, sin θ - sin φ cos0 - cos φ cos θ / the vector d 'observation (Y) presenting as expression:

in which :

corresponds to measurements of the three components of ground speed, and - zGm corresponds to a measurement of geometric altitude.
[7" id="c-fr-0007]
7. Method according to claim 6, characterized in that the lateral component v of the air speed V is assumed to be zero.



[8" id="c-fr-0008]
8. Method according to any one of claims 1 to 7, characterized in that the determination of the common status and of the status associated with the other sensors of the substep (E41) for detecting a faulty sensor comprises the following substeps: - a sub-step (E411) of allocation to each residue of a maximum limit (η +) and a minimum limit (rf) from the estimated flight parameters; the sub-step (E411) also being a sub-step for constructing a first validity indicator (VPs) associated with the static pressure sensor and a second validity sensor (VPt) associated with the total pressure sensor at from the estimated parameters and measurements from the aircraft sensors: o the first validity indicator (VPs) equal to 1 if the relation | £ h (s) (zPm - zGJ | <lPs is verified, the first validity indicator (VPs) equal to 0 if the relation | Ai (s) (zPm _zGm) | lps is not verified, in which lPs corresponds to a limit determined experimentally as a function of the dynamics of the aircraft (AC), corresponding to the function do transfer of a high-pass filter, where the second validity indicator (VPt) being worth 0 by default and 1 if the residue crosses its respective limits, at an instant tk, determined subsequently and that 3n e M such that tn e [tk -xPT, tk] checking | (1 - £ τ) (μΡτ (ϊπ) - ΜΡτ (ΐη _ {)) | <1Ρτ, with τΡτ a time constant, a transfer function of a low-pass filter having as time constant τ, j e M a constant, and 1Pt a limit determined experimentally as a function of the dynamics of the aircraft; residue indicators (R;) being calculated and associated with each residue (η) and validity indicators (Vk); - a sub-step (E412) for identifying the appearance of faults when the sum of the residual indicators (Σ Rj) is strictly greater than zero and identifying, in the event of a fault, the faulty sensor by comparing the current values residue indicators to those listed in a table identified offline or online listing the failure cases according to the different combinations of value of the residue indicators (Rj).
[9" id="c-fr-0009]
9. Method according to any one of claims 1 to 8, characterized in that the statuses associated with each of said sensors (C1, C2, CN) are also determined from auxiliary statuses associated with each of said sensors capable of being sent to the detection module (5) by a monitoring module (9).
[10" id="c-fr-0010]
10. Method according to any one of claims 1 to 9, characterized in that, for a consolidated flight parameter measured from a plurality of sensors, the method comprises the following substeps implemented by a module unit verification (10), when a failure is detected for a sensor measuring said flight parameter, said measurement of which is used at the input of the estimation module (4): - a sub-step (E61) of reconfiguration of the sub-module estimation not to take into account the erroneous measurement of the flight parameter used until then in the estimation sub-step (E22), - a sub-step (E62) for calculating the difference between the estimation of said flight parameter and the measurement of one of said sensors from the plurality of sensors, for each of the measurements from the plurality of sensors, if the absolute value of the difference is less than a predetermined value, the measurement being retained in the estimation sub-step (E22).
[11" id="c-fr-0011]
11. Monitoring and estimation device: - parameters relating to the flight of an aircraft (AC); - sensor statuses, these statuses being representative of an operation of said sensors (C1, C2, ..., CN); and - a status of a parameter (P1) corresponding to the current mass of the aircraft (AC), this status being representative of the validity of said parameter (P1), characterized in that it comprises: - a module initialization (3), configured to initialize the statuses of sensors (C1, C2, ..., CN) configured to determine parameters relating to the flight of the aircraft (AC) as well as the status of the corresponding parameter (P1) to the current mass of the aircraft and to initialize parameters used during the implementation of the monitoring and estimation device (1); the monitoring and estimation device (1) further comprises the following modules, implemented iteratively: - an estimation module (4), configured to determine an estimate of the values of the parameters relating to the flight of the aircraft (AC) as well as an estimate of an error of the parameter (P1) of current mass, from: o measurements of the parameters relating to the flight provided by the sensors (C1, C2, ..., CN), o parameters relating to the flight initialized in the initialization step (E1) or estimated at the previous iteration of the estimation step (E2) and o the statuses associated with each of said sensors (C1, C2, ... , CN), the estimation module (4) also being configured to generate residues (η) which are functions of the values of the parameters relating to the flight measured and estimated and of innovation terms which correspond to the difference between a value of measured flight parameter and said estimated value; - a first transmission module (7) configured to: o transmit to a user device (6) and to a detection module (5) a signal representative of the estimation of the values of the parameters relating to the flight of the aircraft (AC ) as well as of the estimation of the error of the parameter (P1) of current mass, determined in the estimation step (E2), o send to said detection module a signal representative of the residues generated in step d estimate (E2) to said detection module (5); - a detection module (5) configured to determine the different statuses associated with each of said sensors (C1, C2, ..., CN) and the parameter (PI) corresponding to the current aircraft mass (AC), from : o of the estimation of the values of the residues determined in the estimation step (E2), o of the estimation of the values of the parameters relating to the flight of the aircraft (AC) determined in the estimation step ( E2), o measurements of the parameters relating to the flight provided by the sensors (C1, C2 ..... CN), o the estimation of the error of the parameter (P1) of current mass determined by the module of estimation (4), o of said statuses determined in the previous iteration or initialized in the initialization step (E1); - a second transmission module (8) configured to transmit to the user device (6) and, on the next iteration, to the estimation module (4) the different statuses associated with each of said sensors (C1, C2, ... , CN) and the status associated with said parameter (P1) corresponding to the current mass.
[12" id="c-fr-0012]
12. Device according to claim 11, characterized in that the estimation module (4) comprises; - an adaptation sub-module (41) configured to determine a variance and / or a boolean of validity associated with each of the measurements of the parameters relating to the flight provided by the sensors (C1, C2, ..., CN) as well as adjustment parameter parameters associated with the estimation algorithm used in an estimation sub-module (42), from; o said measurements of the parameters relating to the flight and o from the statuses associated with each of said sensors (C1, C2 ..... CN); the adaptation sub-module (41) also being configured to correct the current mass of the aircraft (AC) on the basis of a mass error estimated at the previous iteration or initialized by the initialization module (3) , and of a status associated with the parameter (P1) corresponding to the mass, - I estimation sub-module (42) configured to determine the estimate of the values of the parameters relating to the flight as well as an estimate of the error of said mass, from: o measurements of the parameters relating to the flight supplied by said sensors (C1, C2 ..... CN), o parameters relating to the flight estimated at the previous iteration or initialized in step ( E1) initialization and o from the variance and / or the boolean validity of each of the measurements of the parameters relating to the flight and of the adjustment parameters determined in the adaptation sub-step (E21), the sub-module (42) also being configured for ur generate residues from estimated and measured flight parameters and innovations.
[13" id="c-fr-0013]
13. Device according to any one of claims 11 or 12, characterized in that the detection module (5) comprises: - a detection sub-module (51) configured to determine: o the common status associated with the sensor (C1 ) configured to measure the angle of incidence (a) of the aircraft (AC) and to the parameter (P1) corresponding to the current mass and o the status associated with the other sensors (C2, C3, ..., CN) , from: o measurements of the parameters relating to the flight supplied by said sensors (C2, C3 ..... CN), o the estimation of the values of the parameters relating to the flight as well as the mass error, o statuses associated with each of said sensors (C2, C3, CN) and with a parameter (P1) corresponding to a current aircraft mass (AC) determined on the previous iteration or initialized by the initialization module (3), o residues; - a validation sub-module (52) configured to determine the status associated with the parameter (P1) corresponding to the current mass and the status associated with the sensor (C1) configured to measure the angle of incidence (a), from : o of the common status associated with the sensor (C1) configured to measure the angle of incidence (a) of the aircraft (AC) and to the parameter (P1) corresponding to the current mass, o of the statuses associated with the other sensors ( C2, C3, ..., CN), o estimated flight parameters, o estimated mass error, o measured flight parameters, o residuals generated in sub-step (E22) of estimation and o of a lift coefficient (CL) provided from an on-board modeling supplied by the parameters relating to the flight estimated and measured by said sensors (C1, C2, ..., CN).
[14" id="c-fr-0014]
14. Aircraft, characterized in that it comprises a device 1 for monitoring and estimating flight parameters of an aircraft (AC), such as that specified under any one of claims 11 to 13.

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同族专利:

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公开号 | 公开日

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US20180340795A1|2018-11-29|

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CN108931258A|2018-12-04|

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FR3066755B1|2019-06-07|

引用文献:

---

公开号 | 申请日 | 公开日 | 申请人 | 专利标题

---

FR2988833A1|2012-03-28|2013-10-04|Dassault Aviat|DEVICE FOR DISPLAYING FLIGHT CHARACTERISTICS OF AN AIRCRAFT, INSTRUMENTATION FOR AIRCRAFT AND ASSOCIATED METHOD|

---

US20140090456A1|2012-09-28|2014-04-03|United Technologies Corporation|Model based engine inlet condition estimation|

---

US20150233730A1|2014-02-18|2015-08-20|Airbus Operations |Method of sensor data fusion|

---

US20160290826A1|2014-10-08|2016-10-06|Honeywell International Inc.|Systems and methods for attitude fault detection based on integrated gnss/inertial hybrid filter residuals|

---

US20190108760A1|2017-10-10|2019-04-11|Honeywell International Inc.|System and method for developing and maintaining temperature-compensated altitude information|

---

US20200201312A1|2018-12-21|2020-06-25|The Boeing Company|Sensor fault detection and identification using residual failure pattern recognition|

---

CN111122899B|2019-12-11|2020-11-17|南京航空航天大学|Incidence angle sideslip angle estimation method for flying in atmospheric disturbance|

---

CN111942602B|2020-08-10|2021-10-08|中国人民解放军海军航空大学青岛校区|Flight parameter data comprehensive processing system|

---

CN112578816B|2021-02-25|2021-05-14|四川腾盾科技有限公司|Estimated arrival time calculation method for large-span-wing large unmanned aerial vehicle|

法律状态:
2018-05-28| PLFP| Fee payment|Year of fee payment: 2 |

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2018-11-30| PLSC| Search report ready|Effective date: 20181130 |

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2019-05-31| PLFP| Fee payment|Year of fee payment: 3 |

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2020-05-30| PLFP| Fee payment|Year of fee payment: 4 |

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2021-05-31| PLFP| Fee payment|Year of fee payment: 5 |

优先权:

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申请号 | 申请日 | 专利标题

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FR1754549|2017-05-23|

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FR1754549A|FR3066755B1|2017-05-23|2017-05-23|METHOD AND DEVICE FOR MONITORING AND ESTIMATING PARAMETERS RELATING TO THE FLIGHT OF AN AIRCRAFT.|FR1754549A| FR3066755B1|2017-05-23|2017-05-23|METHOD AND DEVICE FOR MONITORING AND ESTIMATING PARAMETERS RELATING TO THE FLIGHT OF AN AIRCRAFT.|

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US15/980,991| US20180340795A1|2017-05-23|2018-05-16|Method and device for monitoring and estimating parameters relating to the flight of an aircraft|

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CN201810470520.7A| CN108931258A|2017-05-23|2018-05-17|Method and apparatus for monitoring and estimating the relevant parameter of flight to aircraft|