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    • 专利摘要:
    Method and device for searching for a fault likely to affect a rotating mechanical power transmission device The method according to the invention comprises: a step of obtaining (E10) a signal that can be modeled by a product of a high frequency signal s1 and a low frequency signal s2, generated by the rotating mechanical power transmission device and acquired by a sensor; A step of determining (E20) estimates of the signals s1 and s2 minimizing a difference between all or part of the signal s and a product of these estimates; A step of analyzing (E30) the estimates of the signals s1 and s2 in order to detect the presence of a fault affecting the rotating mechanical power transmission device; if a fault is detected at the end of the analysis step (E40), a step of locating (E50) said fault from at least one of the estimates of the signals s1 and s2.
    公开号:FR3069668A1
    申请号:FR1757165
    申请日:2017-07-27
    公开日:2019-02-01
    发明作者:Axel BARRAU；Elisa Hubert；Mohamed El Badaoui
    申请人:Safran SA；
    IPC主号:
    专利说明:

    Invention background
    The invention relates to the general field of monitoring (also called "health monitoring" in English) of rotating mechanical machines, such as in particular rotating mechanical machines commonly used in the aeronautical industry.
    It relates more particularly to the search for faults (eg wear, crack, etc.) likely to affect a rotating mechanical power transmission device (eg gear, ball bearing, motor, etc.), from signals (eg vibratory, acoustic or instantaneous speed) generated by this mechanical device during its use.
    At present, the maintenance of mechanical rotating power transmission devices such as those used in aeronautics is mainly based on a visual and endoscopic inspection of these devices. When designing these devices, a number of operating hours (eg flight hours when the device is installed in an aircraft) after which maintenance is recommended is calculated taking into account relatively large safety margins. However, this approach suffers from several shortcomings.
    Indeed, a rotating device in perfect condition can be disassembled for verification and then reassembled inappropriately or imprecisely. Conversely, such an approach does not allow rapid detection of a rotating device which would have deteriorated soon after its assembly, which could endanger the users of the system in which it is installed.
    In addition, a visual and endoscopic inspection as it is currently practiced is a relatively long and tedious operation, which mobilizes for a considerable time the system (eg aircraft engine) in which the device is installed. This inspection also depends on an operator, and can therefore be a source of errors.
    To overcome these drawbacks and in particular allow precise and early detection of faults likely to affect a rotating machine, it is known to monitor such a machine by using vibratory monitoring of the machine. The vibrations (or vibrational signals) generated by such a rotating machine during its operation indeed represent a very relevant signature of its state of health, instantly reflecting any change affecting its structure or its operating regime. These signals can be acquired from sensors positioned on or near the monitored rotating machines, such as for example accelerometers, etc.
    Vibration monitoring is therefore particularly effective for the detection of faults or malfunctions affecting rotating machines. It is conventionally based for this purpose on the analysis of standard indicators extracted from the vibrational signals generated by the rotating machines such as for example their peak-to-peak amplitude, their power, their statistical moments or even the amplitude of their harmonics. .
    A major issue in vibration monitoring techniques today lies in the location of detected faults, especially when the rotating machine in which we are interested is a system composed of several rotating elements. The separation, in the acquired vibrational signal, of the contributions of the different elements advantageously makes it possible to easily locate the fault detected on the rotating machine.
    The document by C. Capdessus et al. entitled "Analysis of the vibrations of a gear: cepstrum, correlation, spectrum", Signal Processing, vol. 8 no. 5, shows that a rotating device such as a gear composed of two toothed wheels rotating at relatively close rotational speeds generates a vibratory signal which can be modeled as the product of two periodic signals (ie functions), and more particularly of a first “high frequency” signal or component representing the meshing and of a second “low frequency” signal or component representing the sum of the contributions of the two gears of the gear.
    Based on this observation, a vibration monitoring method known from the state of the art applied to such a gear consists in filtering, by means of a bandpass filter, the spectrum of the vibratory signal generated by the gear around the frequency of meshing of the gear (preferably around the dominant harmonic concentrating the most energy). The spectrum thus obtained is then brought back around the zero frequency. The time signal corresponding to the spectrum brought around the zero frequency is proportional to the low frequency component of the vibratory signal generated by the gear, in other words to the second signal representing the sum of the contribution of the two cogwheels of the gear. The filtering of this signal proportional to the second signal makes it possible to extract the contribution of each toothed wheel of the gear. Each contribution can then be analyzed separately, using in particular the aforementioned indicators (peak-to-peak amplitude, statistical moments, etc.), with a view to looking for the presence of a possible defect affecting the associated toothed wheel. Note that all of these operations are generally performed directly on the time signal.
    This method is particularly effective when the energy of the vibratory signal is concentrated on a single harmonic. However, when several harmonics are visible in the spectrum of the vibrating signal, the bandpass filtering performed ignores a large part of the information carried by the vibrating signal. This results in imprecision in the indicators calculated and used to detect faults, thus tarnishing the reliability of the detection carried out.
    Subject and summary of the invention
    The main object of the present invention is to overcome the aforementioned drawbacks and proposes a method for finding a fault capable of affecting a rotating mechanical power transmission device, comprising:
    A step of obtaining a signal s which can be modeled by a product of a high frequency signal si and of a low frequency signal s2, generated by the rotating mechanical power transmission device and acquired by a sensor;
    A step of determining estimates of the signals si and s2 minimizing a difference between all or part of the signal s and a product of these estimates;
    A step of analyzing the estimates of the signals si and s2 with a view to detecting the presence of a fault affecting the rotating mechanical power transmission device;
    - If a fault is detected at the end of the analysis step, a step of locating said fault from at least one of the estimates of the signals si and s2.
    Correlatively, the invention relates to a device for finding a fault capable of affecting a rotating mechanical power transmission device, the device comprising:
    - an obtaining module configured to obtain a signal s which can be modeled by a product of a high frequency signal si and a low frequency signal s2, generated by the rotating mechanical power transmission device and acquired by a sensor;
    A determination module, configured to determine estimates of the signals si and s2 while minimizing a difference between all or part of the signal s and a product of these estimates;
    - an analysis module, configured to analyze the estimates of the signals si and s2 with a view to detecting the presence of a fault affecting the rotating mechanical power transmission device; and a localization module, activated if a fault is detected by the analysis module, configured to locate said fault from at least one of the estimates of the signals si and s2.
    The invention also relates to a non-destructive control system of a rotating mechanical power transmission device comprising:
    - a sensor configured to acquire a signal s which can be modeled by a product of a high frequency signal si and a low frequency signal s2, and generated by the rotating mechanical power transmission device;
    - A fault finding device capable of affecting the rotating mechanical power transmission device according to the invention, and configured to obtain and use the signal s acquired by the sensor.
    The invention therefore proposes a vibration monitoring technique based on a demodulation of the signal s generated by the observed rotating mechanical device, while dispensing with bandpass filtering as practiced in the prior art. It is noted that no limitation is attached to the nature of the signal s since it can be modeled as a product of two high and low frequency signals. The signal s can in particular be a vibratory signal, an acoustic signal or even an instantaneous speed signal.
    To this end, the invention proposes replacing the filtering step implemented in the prior art with an optimization step: this optimization step consists in minimizing the difference between all or part of the signal s generated by the rotating mechanical device, which can be modeled by the product of two signals si and s2, and a product of the estimates of the signals si and s2. The estimates of the signals si and s2 thus obtained at the end of the optimization step allow better reconstruction of the signal s acquired by the sensor. From the estimates obtained from the signals si and s2 during the optimization step, the contribution of each element of the mechanical device rotating in the signal s acquired can then be easily and more precisely identified, allowing easy localization on one at least of these elements of the fault or faults detected if necessary on the device.
    The implementation of an optimization step overcoming a filtering of the signal in accordance with the invention advantageously makes it possible to exploit all the useful information contained in the vibratory signal s and leads to a very precise estimation of the signals if and s2. The invention thus provides a precise and reliable monitoring technique which can be easily applied to any type of rotating mechanical power transmission device as soon as the signals (for example vibratory or acoustic or instantaneous speed signals) generated by it. these can be modeled by the product of a low frequency signal and a high frequency signal as mentioned above. Such a rotating mechanical device is typically a gear formed by two gears as described above, but the invention also applies to other types of mechanical rotating power transmission devices, such as for example a heat or electric motor. asynchronous, to a ball bearing, etc.
    It should be noted that the monitoring technique proposed by the invention advantageously requires the use of only one sensor to locate a fault detected if necessary on the observed rotating mechanical device, which facilitates its implementation.
    In a particular embodiment, the search method according to the invention comprises:
    - a step of obtaining kinematic parameters of the rotating mechanical power transmission device;
    A step of determining, from said kinematic parameters, a duration of analysis of the signal s, said duration of analysis being an integer multiple of a period of the low frequency signal s2;
    and in which the estimates of the signals si and s2 are determined from a sequence resulting from the signal s and of duration equal to the duration of analysis.
    Taking into account, for the estimation of the signals s 1 and s 2, of a sequence of the signal s acquired of duration equal to the duration of analysis advantageously allows implementation of the invention in real time. The use of a sequence of duration which is an integer multiple of a period of the low frequency signal s2 makes it possible to obtain a spectrum having several harmonics around each of which is a series of more or less spread "peaks" corresponding to the spectrum of the low frequency signal s2. This form of the spectrum can be easily exploited during the optimization step implemented by the invention. However, such a spectrum can advantageously be obtained in this embodiment even if the analysis duration is chosen to be relatively short (for example equal to twice the period of the low frequency signal), which makes possible a real-time implementation of the method. proposed by the invention.
    In a particular embodiment, the search method further comprises a step of resampling the sequence from the vibratory signal with a regular step equal to a fraction of the analysis time, before using it to determine the estimated signals si and s2.
    This resampling step advantageously makes it possible to obtain series of peaks around each harmonic of the spectrum which are in the form of series of diracs. The information contained in these series of diracs is therefore more easily exploitable (the peaks are not spread by side effect) and makes it possible to improve the precision of the estimation of the signals si and s2 carried out by the invention.
    In a particular embodiment, the search method comprises, during the step of determining the estimates of the signals si and s2:
    A step of obtaining a discrete Fourier transform (or TFD) of the sequence originating from the signal s, this discrete Fourier transform comprising a plurality of harmonics;
    A step of constructing a matrix M (S) from the discrete Fourier transform obtained, the dimensions of the matrix depending on a number of harmonics determined for the signal si and on a number of harmonics determined for the signal s2, each component of the matrix comprising an amplitude of a harmonic of the discrete Fourier transform obtained;
    A step of approximation of rank 1 of the matrix M (S) and of obtaining discrete Fourier transforms of the estimates of the signals si and s2.
    This embodiment offers a very simple way of implementing the optimization step allowing the determination of the estimates of the signals si and s2, without loss of useful information. Such an optimization is indeed a non-linear and non-quadratic problem under constraints which can prove difficult to solve, in particular in an embedded and real-time context. Thanks to the step of resampling the acquired signal s and to the rearrangement of the resampled spectrum in matrix form (ie in the form of matrix M (S)), this optimization problem can be reduced to an optimal approximation of rank 1 which can be easily resolved.
    To achieve the rank 1 approximation of the matrix M (S), different techniques can be used.
    Thus, in a particular embodiment:
    - the rank 1 approximation step of the matrix M (S) uses a decomposition into singular values of the matrix M (S), said decomposition providing a first singular vector to the left of the matrix M (S), a first singular vector to the right of the matrix M (S) and a first singular value of the matrix M (S); and - the discrete Fourier transform of the estimate of the signal si is obtained from the first singular vector to the left of the matrix M (S) and the discrete Fourier transform of the estimate of the signal s2 is obtained from the first vector to the right of the matrix M (S), one and / or the other of the first singular vectors to the left or to the right being weighted, a product of the weights applied being equal to the first singular value of the matrix M (S ).
    It is noted that, within the meaning of the invention, the estimates of the signals si and s2 determined during the determination step are not necessarily determined in the time domain, but can be determined in the frequency domain. Thus the discrete Fourier transforms of the estimate of the signal si and of the estimate of the signal s2 constitute estimates of the signals si and s2 within the meaning of the invention, taking into account the known relation linking a time signal to its spectrum and more specifically to its discrete Fourier transform. It is therefore not necessary to proceed with the analysis of the estimates of the signals si and s2 and the search for faults affecting the rotating mechanical device to go back into the time domain by transforming, via for example an inverse Fourier transform, the transforms of discrete Fourier obtained during the obtaining stage.
    In addition, the spectra considered and obtained are not necessarily complete. They can be partial and include only the frequencies useful for the invention (typically the harmonics of the signal si and its modulations by the harmonics of the signal s2). Within the meaning of the invention, the term spectrum includes these different configurations (full spectrum or only partial spectrum).
    Thus, in a particular embodiment, the step of analyzing the estimates of the signals si and s2 is carried out directly from the Fourier transforms of the estimates of the signals si and s2 obtained during the obtaining step.
    In an alternative embodiment, the step of determining the estimates of the signals si and s2 further comprises a step of transformation in the time domain of the discrete Fourier transforms obtained from the estimates of the signals si and s2.
    The choice to directly analyze the estimates of the signals si and s2 in their temporal forms or in their frequency forms depends on the indicators considered to search for the faults likely to affect the rotating device.
    In a particular embodiment, the search method comprises at least one step of filtering the signal s2 making it possible to identify contributions to the vibratory signal of different elements of the mechanical device, said identified contributions being used during the step of locating d '' a fault detected at the end of the analysis step.
    This step makes it possible, from the signal s2, to isolate the contribution of each element of the rotating device liable to be affected by a fault and to facilitate the location of this fault. Each contribution thus isolated is analyzed independently of one another (by calculating for example the indicators mentioned previously on this contribution), with a view to detecting whether it presents an anomaly. Where appropriate, the location of a fault on the element corresponding to the contribution analyzed is direct.
    As mentioned previously, the invention applies to the search for faults affecting any type of rotating mechanical power transmission device, since the vibrational signals generated by these devices can be modeled in the form of a product of a low frequency signal and a high frequency signal. The invention thus has a preferred but non-limiting application in the field of aeronautics which uses numerous rotating devices verifying this hypothesis, such as for example gears comprising two toothed wheels, ball bearings, etc., notably equipping aircraft and more particularly aircraft engines.
    In a particular embodiment, the steps of the search method according to the invention are determined by instructions from computer programs.
    Consequently, the invention also relates to a computer program on an information or recording medium, this program being capable of being implemented in a search device or more generally in a computer, this program comprising instructions adapted to the implementation of the step of determining the non-destructive testing method as described above.
    This program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.
    The invention also relates to an information or recording medium readable by a computer, and comprising instructions of a computer program as mentioned above.
    The information medium can be any entity or device capable of storing the program. For example, the support may include a storage means, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or else a magnetic recording means, for example a floppy disk or a disc. hard.
    On the other hand, the information medium can be a transmissible medium such as an electrical or optical signal, which can be routed via an electrical or optical cable, by radio or by other means. The program according to the invention can in particular be downloaded from a network of the Internet type.
    Alternatively, the information medium can be an integrated circuit in which the program is incorporated, the circuit being adapted to execute or to be used in the execution of the process in question.
    Brief description of the drawings
    Other characteristics and advantages of the present invention will emerge from the description given below, with reference to the appended drawings which illustrate an embodiment thereof devoid of any limiting character. In the figures:
    - Figure 1 shows, in its environment, a non-destructive control system according to the invention, in a particular embodiment;
    - Figure 2 shows the hardware architecture of a search device according to the invention, belonging to the non-destructive control system of Figure 1;
    - Figure 3 shows, in the form of a flowchart, the main steps of a search method according to the invention, as implemented by the search device of Figure 2; and - Figures 4 and 5 show examples of Fourier transforms of signals that can be used during the search method according to the invention.
    Detailed description of the invention
    FIG. 1 represents, in its environment, a non-destructive control system 1 according to the invention, in a particular embodiment.
    The system 1 is configured to perform non-destructive testing of a rotating mechanical power transmission device 2. In the example envisaged in FIG. 1, the rotating mechanical device 2 is a gear made up of two toothed wheels RI and R2 with straight teeth capable of transmitting power, such as those conventionally used in the aeronautical industry and which equip aircraft engines.
    The toothed wheels RI and R2 are elements of the mechanical device 2 within the meaning of the invention. The gear wheel RI has an integer number NI of teeth, and the gear wheel R2 has an integer number N2 of teeth. NI and N2 are assumed to be known. It is also assumed that the period Te of the meshing which separates, when the gear 2 is in action, two consecutive teeth is known.
    It should be noted that the invention is not limited to this type of gears or even to gears, and can be applied to other rotary mechanical power transmission devices, such as for example ball bearings, asynchronous thermal or electric motors, etc.,
    In known manner, such a mechanical rotating power transmission device generates, when in action, a time signal noted s, of deterministic type, and whose parameters are linked to the kinematics of the rotating mechanical device. This signal s (t) is here a vibratory signal which can be modeled in the form of a product of a signal noted if high frequency and of a signal noted s2 low frequency, that is to say:
    s (t) = sl (t) x s2 (t) (Eq. 1)
    As a variant, signals other than vibratory signals can be envisaged since they can be modeled like the signal s in the form of a product of two signals si and s2. Thus, in particular, the signal s (t) can be an acoustic signal (translating the vibrations of the air generated by the rotating mechanical device) or an instantaneous speed signal measured by a sensor positioned on one of the rotating shafts.
    The high frequency signal si is a periodic signal having the same frequency as the meshing. The low frequency signal s2 can be written, in the example of the gear consisting of two toothed wheels RI and R2 envisaged here, in the form:
    s2 (t) = l + sRl (t) + sR2 (t) (Eq. 2) where sRl (t) denotes a signal of the same frequency as the rotation frequency of the toothed wheel RI and sR2 (t) denotes a signal of the same frequency as the frequency of rotation of the toothed wheel R2. In other words, the signal sl (t) is amplitude modulated both by a periodic signal sRl (t) of period equal to the rotation period of the toothed wheel RI and by a periodic signal sR2 (t) of period equal to the period of rotation of the toothed wheel R2.
    Thus, schematically in this modeling, the signal sl (t) represents an "average" signal generated by the gear in action, the signal sRl (t) a disturbance of the signal sl (t) caused by the defects (cracks, imperfections, etc.) affecting the gear RI and the signal sR2 (t) a disturbance of the signal sl (t) caused by the defects (cracks, imperfections, etc.) affecting the gear R2. The signals sR1 (t) and sR2 (t) characterize the contributions to the vibration signal of the toothed wheels RI and R2 within the meaning of the invention.
    According to the invention, the non-destructive control system 1 performs a non-destructive control of the gear 2 from the vibratory signal s (t) generated by it when it is in action. To this end, it is equipped with a sensor 3, located near the gear 2 so as to measure and acquire the signal s (t). The sensor 3 is for example an accelerometer or a microphone. Its placement near the gear 2 to allow it to acquire the vibratory signal generated by the latter poses no difficulty for the skilled person (it is placed for example as close as possible to a bearing supporting one of the axes of the wheels of the gear), and depends on the rotating mechanical device considered and on the context of use of the latter. It is not described in detail here.
    The vibratory signal s (t) acquired by the sensor 3 is transmitted to a device 4 of the non-destructive control system 1 capable of processing this signal and analyzing it in particular with a view to detecting the presence of a possible fault on the gear 2. The device 4 is a fault finding device according to the invention.
    In the embodiment described here, the search device
    4 has the hardware architecture of a computer, as illustrated in FIG. 2.
    It includes in particular a processor 5, a random access memory 6, a read-only memory 7, a non-volatile flash memory 8 as well as communication means 9 allowing in particular the search device 4 to communicate in particular with the sensor 3 to obtain the vibratory signal generated by gear 2 and acquired by it. These communication means include, for example, a digital data bus if the search device 4 is embedded in the same equipment as the gear 2 (eg on board an aircraft), or a communication interface on a telecommunications network. , etc.
    The read-only memory 7 of the search device 4 constitutes a recording medium according to the invention, readable by the processor 5 and on which a computer program PROG according to the invention is recorded.
    The computer program PROG defines functional and software modules 20 here, configured to implement a method of searching for possible faults affecting the gear 2 according to the invention. These functional modules are based on and / or control the hardware elements 5-9 of the research device 4 mentioned above. They notably include here, as illustrated in FIG. 1:
    - an obtaining module 4A configured to obtain the vibratory signal s measured by the sensor 3 and generated by the gear 2 in action, this module relying on the communication means 9;
    A determination module 4B, configured to determine estimates of the signals si and s2 whose product minimizes a difference with the vibratory signal s;
    - an analysis module 4C, configured to analyze the estimates of the signals si and s2 determined by the determination module 4B with a view to detecting the presence of a fault affecting the rotating mechanical power transmission device; and a localization module 4D, activated if a fault is detected by the analysis module 4C, configured to locate said fault from at least one of the estimates of the signals si and s2.
    In the embodiment described here, the search device 4 also has a notification module 4E, capable of notifying a user or a remote device of the existence of a fault on the gear if necessary. This notification module 4E can rely in particular on the communication means 9 of the search device 4 or on input / output means thereof, such as for example a screen or a microphone capable of signaling the detection of a fault with a user installed near the search device 4.
    The functions of these different modules are described in more detail now with reference to the steps of the search method according to the invention.
    FIG. 3 illustrates, in the form of a flowchart, the main steps of a search method according to the invention in a particular embodiment in which it is implemented by the search device 4 of the non-destructive control system 1 .
    It is assumed as a preliminary to this process, that the gear 2 is put into action with an engagement period Te, and generates a vibratory signal s (t) as described above.
    This vibratory signal s (t) is acquired by the sensor 3 over a predetermined measurement duration denoted Tacq, and supplied to the search device 4. The vibratory signal s (t) is here a sampled signal comprising a plurality Nech of corresponding samples at sampling instants ti, ..., t Ne ch multiple of a sampling period Tech.
    For example, we choose Tacq equal to once the period of the low frequency signal s2. As a variant, Tacq can be chosen to be equal to several periods of the low frequency signal s2 to allow filtering of the noise present in the signal.
    The vibratory signal s (t) is obtained by the module 4A for obtaining the search device 4 via in particular the communication means 9 fitted to the search device 4 (step E10). The obtaining module 4A supplies the vibratory signal s (t) obtained to the determination module 4B for processing.
    As mentioned previously, the vibratory signal s (t) generated by the gear 2 and acquired by the sensor 3 is remarkable in that it can be modeled as the product of a high frequency signal si and a low frequency signal s2 (cf. equation (Eq. 1) above). By high frequency signal and low frequency signal, it is meant here that the high frequency signal si is periodic and has a frequency higher than the low frequency signal s2 which is also periodic. The low frequency signal s2 furthermore comprises, as shown in equation (Eq. 2), the contribution sR1 due to the toothed wheel RI and the contribution sR2 due to the toothed wheel R2. The processing of the vibratory signal s (t) by the determination module 4B consists in determining an estimate of each of the signals si and s2 in order to be able to analyze them to detect the presence, if necessary, of a defect affecting the gear.
    To this end, the determination module 4B, unlike the 15 treatments known from the state of the art, does not perform sub-optimal bandpass filtering around the gear engagement frequency to extract the low signal. frequency s2. But it determines the estimates of the signals si and s2 (denoted respectively si and s2) by minimizing a difference between the vibratory signal s (t) and the product of these 20 estimates, that is to say by solving the following optimization problem (step E20) :
    (si, s2) = argmin (ïï ï ; i 2) (Ση = ιΙΙ $ (ίη) “Wn) s2 (tn) ll 2 ) (Eq. 4) where the estimates of the signals si and s2 are sought on the set of periodic functions of period Te and T2 respectively.
    The inventors have found that in a particularly advantageous embodiment, this optimization problem could be solved very simply via matrix processing by means of a few simple preprocessing operations carried out on the vibratory signal s (t).
    As a variant, other techniques for solving the optimization problem mentioned in equation (Eq. 4) can be used by the determination module 4B, such as for example a gradient descent, a Newton or Gauss- method. Newton, symbolic methods, an extended Kalman filter, a stochastic gradient descent, etc.
    In the embodiment described here, in order to determine the estimates of the signals si and s2 in a simple manner, the determination module 4B first performs a resampling of the signal s (t) (step E21).
    To this end, the determination module 4B firstly determines, from the kinematic parameters of the gear 2, and more particularly from the number NI of teeth of the toothed wheel NI, of the number N2 of teeth of the toothed wheel N2 , and of the mesh period Te of the gear 2, a duration of analysis Tmax of the vibratory signal s (t).
    It is assumed here that these kinematic parameters of the gear 2 have been communicated to the search device 4 beforehand, for example by an operator supervising the non-destructive testing carried out by the non-destructive testing system 1, and are stored for example in its memory non-volatile 8.
    As a variant, these parameters can be obtained by the search device 4 by interrogating a user via the input / output means of the search device 4, or the search device 4 could have been configured beforehand with these parameters, in particular when it is on board and intended to operate independently without the intervention of an operator.
    Note that the numbers of teeth NI and N2 depend on the gear 2 and are therefore fixed and known in advance. The engagement period Te depends on the engine speed: it can either be fixed in advance and imposed on the engine, or provided by an operator or user as mentioned above, or even be evaluated by an additional module provided for this effect.
    The duration of analysis Tmax determined by the determination module 4B is taken here equal to an integer multiple Nmax of the period denoted T2 of the low frequency signal s2 (Nmax is an integer greater than or equal to 1), ie Tmax = Nmax x T2 . For a gear consisting of two toothed wheels Rl and R2 as envisaged in FIG. 1, the period T2 of the low frequency signal s2 is equal to:
    T2 = NtotxTe where Ntot denotes the smallest common multiple of NI and N2.
    The choice of Nmax depends of course on the duration Tacq of acquisition of the vibratory signal s (t) by the sensor 3 and on the context of application of the invention: it is well understood indeed that if a real time application is desired, a small number Nmax will preferably be chosen. Conversely, the larger Nmax is chosen, the lower the noise affecting the signal.
    Then, the determination module 4B extracts from the vibratory signal s (t) which has been transmitted to it a sequence denoted s'of duration equal to the analysis duration Tmax (step E21). It then resamples the sequence thus extracted with a regular step equal to a fraction of the analysis time Tmax (step E22), that is:
    AT = Tmax / n (Eq. 3) where n denotes a predetermined number of samples. This resampling is carried out using a standard interpolation technique, such as for example a linear interpolation technique, or a Whittaker-Shannon technique, etc. The resampled sequence obtained is noted sr.
    The choice of the integer n results from a compromise: the larger n is chosen, the more the information loss linked to the resampling is limited but the higher the computation complexity linked to the resampling. We note however that it is useless to choose n greater than T2 / Tech (Tech designating the sampling period of the signal s) because there is then no more information gain.
    We note that if the resampling step considered is regular, it does not necessarily remain constant over time: a step as defined by the equation (Eq. 3) indeed adapts advantageously to the speed of rotation of the wheels and of the meshing (ie the resampling carried out is an “angular” sampling, determined by the variation of angle of the wheels). If the wheels accelerate, the resampling step varies for a constant number n of samples.
    Thanks to this resampling, and taking into account the characteristics of the vibratory signal s (t), it is ensured that the spectrum of the resampled sequence sr of duration Tmax extracted from the vibratory signal s (t) is composed of 'a series of harmonics corresponding to the high frequency signal if, each harmonic being surrounded by diracs corresponding to the pattern of the spectrum of the low frequency signal s2. We note that in the absence of resampling, the diracs are replaced by more or less spread out “capitals”, which has the effect of introducing a noise which should be taken into account when processing the signal. vibratory (for example by approximating each marquee by a dirac).
    The inventors had the judicious idea of using at the level of the determination module 4B the resampling sequence born sr as an approximate version of the vibratory signal s (t) to solve the optimization problem given by the equation (Eq. 4), and to exploit the property of the spectrum of this sequence stated above to simplify the resolution of the optimization problem.
    Indeed, the equation (Eq. 4) can be written, in the spectral domain, in the form:
    (SÏ, S2) = argminsï'Sï (| Sr “ S2 |) (Eq. 5) where n denotes the number of samples previously introduced during the resampling step E22, and Sr, SÏ, S2 denote respectively the discrete Fourier transforms of the signals sr, sï and s2, | | denotes a Euclidean norm, and * the convolution operator. Here we use a vector representation of the discrete Fourier transforms Sr, sï, S2 and the following convention if E () denotes the integer function: the harmonic 0 is at the position E ((n + l) / 2) in the vector Sr, the harmonic 1 is at the position E ((n + l) / 2) + l, the harmonic -1 is at the position E ((n + 1) / 2) -1, etc. .
    However, as thanks to the resampling carried out during step E21, all the signals present themselves in the spectral domain in the form of series of diracs, the convolution present in the equation (Eq. 5) does not include “at each operation »Only one term. The problem of optimizing the equation (Eq. 5) is thus equivalent to the problem defined by the following equation (Eq. 6):
    (M (SÏ), M (S2)) = argmm M (51) | M (52) (| m (S) - ± M (Sl) .M (S2y | ζ) (Eq. 6) where M (S) denotes a matrix whose components correspond to the amplitudes of the diracs of the discrete Fourier transform Sr, M (S1) a column vector whose components correspond to the amplitudes of the diracs of the discrete Fourier transform SÏ (in other words it is the column vector obtained by removing from the vector SI the inputs which do not correspond to the harmonics of the signal si), M (S2) a column vector whose components correspond to the amplitudes of the diracs of the discrete Fourier transform S2 (in other words it is the column vector obtained by removing from the vector S2 the inputs which do not correspond to the harmonics of the signal s2), and | | Fr o denotes the Froebenius matrix norm, known per se and not recalled here. The solution of the problem defined by the equation (Eq. 6) can be obtained in a known way from the first singular value of the mat rice M (S), as described in more detail below.
    Thus, following the resampling carried out in step E22, the determination module 4B determines the discrete Fourier transform Sr of the resampled sequence sr (step E23).
    FIG. 4 illustrates the shape of the Fourier transform Sr obtained, in the absence of noise. We distinguish in this figure four harmonics Hl, H2, H3 and H4 (corresponding to the harmonics of the high frequency signal if), each harmonic being surrounded on either side symmetrically by a set of diracs (three diracs in the figure 4 present on each side of each harmonic). The sets of diracs located on either side of each harmonic of the high frequency signal if correspond to the harmonics of the spectrum of the low frequency signal s2.
    From this “spectrum” of diracs obtained, the determination module 4B builds a matrix M (S) (step E24) whose dimensions depend on an integer denoted by nhl of harmonics determined for the high frequency signal si, and of an integer nh2 of harmonics determined for the low frequency signal s2. In the embodiment described here, the matrix M (S) has (l + 2nhl) lines and (l + 2nh2) columns, the components of the matrix M (S) corresponding to the amplitudes of diracs selected in the discrete Fourier transform Sr.
    The numbers of harmonics nhl and nh2 considered for each of the signals si and s2 respectively depend on the type of rotating device considered, and a fortiori, on the type of gear considered in the example of FIG. 1. If a fault affects the gear considered, the number of harmonics present in the discrete Fourier transform Sr for the signals si and s2 can increase, and it is necessary to consider numbers nhl and nh2 large enough to not lose information during the processing of the transform of discrete Fourier Sr. On the contrary, the more good the vibratory signal generated by the gear, the less harmonics there are in the discrete Fourier transform. The numbers nhl and nh2 can be determined experimentally, by testing various gears affected by various faults.
    The inventors have found, experimentally, that a number nhl approximately equal to 10 and a number nh2 of between 8 and 12 corresponded to a good compromise for covering many gears, regardless of the number of teeth of the toothed wheels constituting these gears.
    The positions of the different harmonics of the signals si and s2 in the discrete Fourier transform Sr are known from the kinematic parameters of the gear 2: they are located at the frequencies -nhl.fl, (-nhl + l) .fl ,. .., fl, ..., nhl.fl for the harmonics of the signal if, and around each of these frequencies at nh2.f2, (-nh2 + l) .f2, ..., f2, .. ., nh2.f2 for the harmonics of the signal s2, the frequencies fl and f2 of the signals si and s2 can be derived from the numbers of teeth NI and N2 and from the engagement period Te according to the expressions:
    fl = l / Te and f2 = l / T2 = fl / Ntot.
    Knowing these positions, the determination module 4B constructs the matrix M (S) by associating with each component of the matrix the value of the amplitude of a dirac (harmonic) of the Fourier transform Sr, ie if M (S) [i, j] denotes the component of the matrix located at the intersection of the i-th row and the j-th column, for i whole number such that i = l, 2,, 2.nhl + l, and j whole number such that j = l, 2, ..., 2.nh2 + l:
    M (S) [i, j] = Sr [N0 + (N. (i-nhl-l) + Ntot (j-nh2-l) J (Eq.7) with N0 = E ((n + l) / 2 ) and N integer checking:
    Tmax
    N = —-— = Nmax. Ntot
    Taking into account the previously introduced notations. The operation performed by the determination module 4B to construct the matrix M (S) is shown diagrammatically in FIG. 5.
    The determination module 4B then computes a rank 1 approximation for the matrix M (S) (rank 1 approximation for the Frobenius norm here). The result of this approximation is a matrix of which all the columns are proportional to each other and which can be written in the form of a product of two terms M (Sï). MÇS2) T , from which it is possible to derive estimates of the spectra of the signals si and s2.
    Several approximation methods can be used for this purpose by the determination module 4B, such as an alternating projection algorithm, an algorithm of alternating variables, or a complete decomposition into singular values. These methods can be adapted for real-time operation.
    In the embodiment described here, the determination module 4B uses to perform the rank 1 approximation of the matrix M (S) a decomposition into singular values of the matrix M (S) (step E25). It obtains, at the end of this decomposition, three matrices U, D and V such that:
    M (S) = UDV h H designating the Hermitian operator, U and V designating unit matrices and D a diagonal matrix comprising the singular values of the matrix M (S). The unitary matrices U and V respectively contain the singular vectors said on the left and the singular vectors said on the right corresponding to the singular values contained in the diagonal matrix D.
    According to such a decomposition (or SVD for “Singular Value Decomposition” in English), the singular values are ordered in descending order in the matrix D. The determination module 4B then extracts from the matrix D, the first singular value noted d of the matrix M (S) (corresponding to the largest singular value of the matrix), and of the matrices U and V, the first singular vector on the left of the matrix M (S) noted u and the first singular vector on the left of the matrix M (S) denoted v corresponding to the first singular value d (step E26).
    Then it obtains from the singular value d and the vectors u and v two vectors representing two spectra:
    M (S1) = d.u and
    MÇS2) = v and corresponding to estimates of the spectra of the signals si and s2 respectively. These two vectors actually contain the estimated harmonics of the signals si and s2.
    The determination module 4B then estimates, from these two vectors, the discrete Fourier transforms S 1 of an estimate of the signal si and S2 of an estimate of the signal s2 in the following manner (step E27):
    SÏ [N0 + i. N] = M (Sl) [nhl + 1 + i] = du [nhl + 1 + i] for i = -nhl, ..., nhl S2 [N0 + i.Nmax] = M (S2) [nh2 + 1 + i.Nmax] = v [nh2 + 1 + i.Nmax] for i = -nh2, ..., nh2 where u [i], respectively v [i], denotes the ith component of the vector u, respectively of the vector v. In other words, the SÏ spectrum includes
    2.nhl + l harmonics whose amplitudes are given to the near singular value by the components of the vector u, and the spectrum §2 includes 2.nh2 + l harmonics whose amplitudes are given by the components of the vector v.
    It is noted that a different convention can be applied by the determination module 4B to derive the discrete Fourier transforms S 1 and S2, namely that the singular value d being only a multiplicative value, it can be indifferently applied to the components of the vector v instead of the components of the vector u, that is:
    Sl [N0 + i. N] = u [nhl + 1 + i] for i = -nhl, ..., nhl
    S2 [N0 + i. Nmax] = d. v [nh2 + 1 + i. Nmax] for i = -nh2, ..., nh2
    It should be noted that the Fourier transforms thus obtained by the determination module 4B correspond to the discrete Fourier transforms of the estimates si and s2 of the signals si and s2 which allow an optimal reconstruction of the signal s from the product of the estimates si and s2 .
    The determination module 4B supplies the Fourier transforms S 1 and S2 to the analysis module 4C of the search device 4 for analysis.
    As a variant, the determination module 4B transforms the discrete Fourier transforms s 1 and S2 in the time domain, by means of an inverse discrete Fourier transform, before transmitting them to the analysis module 4C. It then transmits directly to the analysis module 4C the estimates s 1 and s 2 of the signals si and s 2.
    The analysis module 4C then applies standard analysis techniques to the estimates of the signals si and s2 which have been transmitted to it by the determination module 4B to detect whether a fault affects the gear 2 (step E30).
    It can first filter the estimate of signal s2 so as to identify the contributions of each of the gearwheels Rl and R2 (ie estimated signals sRl and sR2 previously introduced), then apply the analysis techniques to each of the contributions thus identified. aforementioned standards. These techniques can be applied either directly to the spectral form of the estimates, or to their temporal form.
    For example, during the analysis step E30, the analysis module 4C can estimate, from the identified contributions, standard failure indicators such as kurtosis, the peak-to-peak amplitude or even the relative amplitude of the harmonics, and compare these indicators with respect to a predetermined threshold (test step E40). The exceeding of the threshold by one of these failure indicators indicates the presence of a fault affecting the gear.
    In addition, if this overshoot is detected on the contribution associated with the toothed wheel R1, the fault is located on the toothed wheel Rl (location step E50 within the meaning of the invention). Conversely, if this overshoot is detected on the contribution associated with the toothed wheel R2, the fault is located on the toothed wheel R2 (step E50 of localization within the meaning of the invention). This location allows targeted and efficient maintenance of the gear.
    In the particular embodiment described here, the fault detected, if any, and its location are notified by the search device via its notification module 4E to an operator in charge of maintaining gear 2. This notification can be done for example by sending a notification message to the operator or to a maintenance system, by displaying a message on a screen of the search device 4, etc.
    The invention therefore provides a very effective method for processing the vibratory signal from a gear, and more generally from a rotating mechanical power transmission device, spurious signals from the environment in which it is installed (e.g. aircraft engine), without resorting to complex source separation methods relying on multiple sensors (as many as possible sources to be separated), and without loss of information resulting from the implementation of an bandpass filtering. The contributions of the various elements of the rotating device to the vibratory signal (ie of the two wheels in the case of the gear considered in the example of FIG. 1) can be studied independently which makes it possible to identify, if necessary, the defective item.
    It is noted that although having been described with reference to a vibratory signal generated by the gear, the invention applies in an identical manner to other types of signals such as for example an acoustic signal or instantaneous speed.
    权利要求:
    Claims (11)
    [1" id="c-fr-0001]
    1. Method for finding a fault capable of affecting a rotating mechanical power transmission device (2), the method comprising:
    A step for obtaining (E10) a signal s which can be modeled by a product of a high frequency signal si and of a low frequency signal s2, generated by the rotating mechanical power transmission device and acquired by a sensor;
    A step of determining (E20) estimates of the signals si and s2 minimizing a difference between all or part of the signal s and a product of these estimates;
    A step of analysis (E30) of the estimates of the signals si and s2 with a view to detecting the presence of a fault affecting the rotating mechanical power transmission device;
    - If a fault is detected at the end of the analysis step (E40), a location step (E50) of said fault from at least one of the estimates of the signals si and s2.
    [2" id="c-fr-0002]
    2. Search method according to claim 1 comprising:
    - a step of obtaining kinematic parameters of the rotating mechanical power transmission device;
    A step of determining, from said kinematic parameters, a duration of analysis of the signal s, said duration of analysis being an integer multiple of a period of the low frequency signal s2;
    and in which, the estimates of the signals si and s2 are determined from a sequence originating from the signal s and of duration equal to the duration of analysis.
    [3" id="c-fr-0003]
    3. The search method as claimed in claim 2, further comprising a step (E22) of resampling the sequence from the signal s with a regular step equal to a fraction of the analysis time, before using it to determine the estimates of the signals si and s2.
    [4" id="c-fr-0004]
    4. Search method according to claim 3, comprising, during the step of determining the estimates of the signals si and s2:
    - a step (E23) of obtaining a discrete Fourier transform of the sequence resulting from the signal s, said discrete Fourier transform comprising a plurality of harmonics;
    - a step (E24) of construction of a matrix M (S) from the discrete Fourier transform obtained, the dimensions of the matrix depending on a number of harmonics determined for the signal si and on a number d harmonics determined for the signal s2, each component of the matrix comprising an amplitude of a harmonic of the discrete Fourier transform obtained;
    A step (E25) of rank 1 approximation of the matrix M (S) and of obtaining discrete Fourier transforms of the estimates of the signals si and s2;
    [5" id="c-fr-0005]
    5. Search method according to claim 4, in which:
    - the rank 1 approximation step of the matrix M (S) uses a decomposition into singular values of the matrix M (S), said decomposition providing a first singular vector to the left of the matrix M (S), a first singular vector to the right of the matrix M (S) and a first singular value of the matrix M (S); and - the discrete Fourier transform of the estimate of the signal si is obtained from the first singular vector to the left of the matrix M (S) and the discrete Fourier transform of the estimate of the signal s2 is obtained from the first vector to the right of the matrix M (S), one and / or the other of the first singular vectors to the left or to the right being weighted, a product of the weights applied being equal to the first singular value of the matrix M (S ).
    [6" id="c-fr-0006]
    6. The search method as claimed in claim 5, in which the step of determining the estimates of the signals si and s2 further comprises a step of transformation in the time domain of the discrete Fourier transforms obtained from the estimates of the signals si and s2.
    [7" id="c-fr-0007]
    7. Search method according to any one of claims 1 to 6 comprising at least one step of filtering the signal s2 making it possible to identify contributions to the vibratory signal of different elements of the mechanical device, said identified contributions being used during the step of locating a fault detected at the end of the analysis step.
    [8" id="c-fr-0008]
    8. The search method as claimed in claim 1, in which the step of analyzing the estimates of the signals si and s2 is carried out from the discrete Fourier transforms of the estimates of the signals si and s2.
    [9" id="c-fr-0009]
    9. Search method according to any one of claims 1 to 8 wherein the mechanical power transmission device is an aircraft gear comprising two toothed wheels.
    [10" id="c-fr-0010]
    10. Device (4) for finding a fault capable of affecting a rotating mechanical power transmission device, the device comprising:
    - an obtaining module (4A) configured to obtain a signal s which can be modeled by a product of a high frequency signal si and of a low frequency signal s2, generated by the rotating mechanical power transmission device and acquired by a captor;
    - a determination module (4B), configured to determine estimates of the signals si and s2 while minimizing a difference between all or part of the signal s and a product of these estimates;
    - an analysis module (4C), configured to analyze the estimates of the signals si and s2 with a view to detecting the presence of a fault affecting the rotating mechanical power transmission device; and - a location module (4D), activated if a fault is detected by the analysis module, configured to locate said fault from at least one of the estimates of the signals si and s2.
    [11" id="c-fr-0011]
    11. System (1) for non-destructive testing of a rotating mechanical power transmission device (2) comprising:
    - a sensor (3) configured to acquire a signal s which can be modeled by a product of a high frequency signal si and a low frequency signal s2, and generated by the rotating mechanical power transmission device;
    - a device (4) for finding a fault capable of affecting the rotating mechanical power transmission device according to claim 10 and configured to obtain and use the signal s acquired by the sensor.
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    同族专利:
    公开号 | 公开日
    US20200232880A1|2020-07-23|
    EP3658881B1|2021-07-07|
    CN111183345A|2020-05-19|
    WO2019020922A1|2019-01-31|
    EP3658881A1|2020-06-03|
    FR3069668B1|2021-02-12|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US6507789B1|2000-07-18|2003-01-14|General Electric Company|Gear transmission condition monitoring method and apparatus|
    US20060150738A1|2004-12-16|2006-07-13|Nigel Leigh|Vibration analysis|
    US20150088435A1|2013-09-24|2015-03-26|Sikorsky Aircraft Corporation|Gear fault detection|
    CN102243140B|2011-04-18|2013-01-23|杨彦利|Mechanical equipment state monitoring method based on sub-band signal analysis|
    NO336991B1|2014-01-10|2015-12-14|Vibsim|Method and apparatus for vibration analysis|
    CN105651376B|2014-11-10|2019-08-06|上海宝钢工业技术服务有限公司|The analysis of mechanical equipment off-line checking system vibration signals spectrograph and alarm method|GB202013058D0|2020-08-21|2020-10-07|Oxford Genetics Ltd|Process for making a recombinant AAV library|
    WO2022038367A1|2020-08-21|2022-02-24|Oxford Genetics Limited|Process for making a recombinant aav library|
    GB202013057D0|2020-08-21|2020-10-07|Oxford Genetics Ltd|Method of making recombinant aavs|
    法律状态:
    2019-02-01| PLSC| Search report ready|Effective date: 20190201 |
    2020-06-23| PLFP| Fee payment|Year of fee payment: 4 |
    2021-06-23| PLFP| Fee payment|Year of fee payment: 5 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1757165|2017-07-27|
    FR1757165A|FR3069668B1|2017-07-27|2017-07-27|METHOD AND DEVICE FOR SEARCHING FOR A FAULT LIKELY TO AFFECT A ROTATING MECHANICAL POWER TRANSMISSION DEVICE|FR1757165A| FR3069668B1|2017-07-27|2017-07-27|METHOD AND DEVICE FOR SEARCHING FOR A FAULT LIKELY TO AFFECT A ROTATING MECHANICAL POWER TRANSMISSION DEVICE|
    CN201880058292.0A| CN111183345A|2017-07-27|2018-07-23|Method and device for searching for defects that can affect a rotary machine power transmission device|
    EP18773524.6A| EP3658881B1|2017-07-27|2018-07-23|Method and device for searching for a defect capable of affecting a rotating mechanical power transmission device|
    PCT/FR2018/051886| WO2019020922A1|2017-07-27|2018-07-23|Method and device for searching for a defect capable of affecting a rotating mechanical power transmission device|
    US16/634,028| US20200232880A1|2017-07-27|2018-07-23|Method and device for searching for a defect capable of affecting a rotating mechanical power transmission device|
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