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    • 专利摘要:
    An integrated health control method of a structure (S) supporting elastic wave propagation modes, comprising the steps of: a) acquiring ambient noise propagating in the structure by means of at least one pair non-co-located elastic wave sensors (CA, CB); b) estimating a function representative of an impulse response of the structure for the elastic propagation between the sensors constituting said pair; c) extracting at least one dispersion curve of the elastic propagation in the structure by time-frequency analysis of this function representative of an impulse response; and d) estimating at least one parameter indicative of a mechanical property of a material constituting the structure from the dispersion curve obtained in step c). System for implementing such a method.
    公开号:FR3060743A1
    申请号:FR1662485
    申请日:2016-12-15
    公开日:2018-06-22
    发明作者:Tom Druet；Bastien CHAPUIS；Emmanuel MOULIN
    申请人:Commissariat a lEnergie Atomique CEA；Commissariat a lEnergie Atomique et aux Energies Alternatives CEA；
    IPC主号:
    专利说明:

    Holder (s): COMMISSIONER OF ATOMIC ENERGY AND ALTERNATIVE ENERGIES Public establishment.
    Extension request (s)
    Agent (s): MARKS & CLERK FRANCE General partnership.
    METHOD AND SYSTEM FOR INTEGRATED HEALTH CONTROL OF A MECHANICAL STRUCTURE BY DIFFUSED ELASTIC WAVES.
    FR 3 060 743 - A1 g Integrated health control method for a structure supporting modes of guided propagation of elastic waves, comprising the following steps:
    a) acquisition of an ambient noise propagating in the structure by means of at least one pair of non-co-located elastic wave sensors (CA, CB);
    b) estimation of a function representative of an impulse response of the structure for the elastic propagation between the sensors constituting said pair;
    c) extraction of at least one dispersion curve of the elastic propagation in the structure by time-frequency analysis of this function representative of an impulse response; and
    d) estimation of at least one parameter indicative of a mechanical property of a material constituting the structure from the dispersion curve obtained during step c). System for implementing such a method.

    METHOD AND SYSTEM FOR INTEGRATED HEALTH CONTROL OF A MECHANICAL STRUCTURE BY DIFFUSED ELASTIC WAVES
    The invention relates to a method of non-destructive testing of a mechanical structure, and more particularly to a method of integrated health monitoring of such a structure. It also relates to a system allowing the implementation of such a process.
    The invention applies to the non-destructive testing of any mechanical structure capable of guiding elastic waves. It can in particular be a beam or tube type structure (providing one-dimensional guidance) or else plate or shell (providing two-dimensional guidance). It can also be a massive structure whose surface is sufficiently regular to allow to guide Rayleigh waves.
    "Beam" is understood to mean an object whose length is large (for example at least ten times greater) than the transverse dimensions. Beams are often used as structural elements, but drive shafts, rails and even cables can also be considered beam type elements.
    The term "plate" means a mechanical structure delimited by two surfaces ("skins") approximately parallel and having a much smaller thickness (at least by a factor of ten) than the smallest lateral dimension. A "shell" is a plate with significant curvature. Plates and shells are widely used in mechanical and civil engineering. For example, the deck of a bridge, a concrete slab, an arch, the fuselage or the wings of an airplane, a tank ... can be modeled by plates or hulls.
    During the lifetime of a structure, the materials from which it is made age. It is therefore important to monitor the state of health of these materials to be sure that the structure can still fulfill its role. Control of the integrity of structures (engineering structures, planes, pipelines, etc.) during their lifetime is generally done during maintenance operations, with human intervention: for this, non-control methods are used. destructive (CND) called "classical", probing the structure by means of ultrasound or electromagnetic fields or, in some cases by subjecting it to elastic deformation.
    A research subject that has been active for a few years aims to integrate sensors at key points in the structure in order to automate the measurement in order to be able to repeat it at regular and generally short intervals and / or to be able to access information on the state of health of certain inaccessible areas, without dismantling or interrupting the operation of the structure. We speak in this case of “integrated health control” (“SHM”, or “Structural Health Monitoring”, that is to say “structural health control”, in the literature in English).
    It has been proposed to carry out an integrated health check using guided ultrasonic waves (OG) emitted and detected by piezoelectric transducers (PZT) integrated in the structure. These guided waves (in the case of plate or shell type structures we speak of "Lamb waves") propagate over a large distance - from a few tens of centimeters to several hundred meters in very favorable geometries such as pipelines - so that a limited number of transducers can control a large area.
    The integrated health control and aging monitoring techniques based on guided waves are typically "active", that is to say that the ultrasonic waves are emitted by dedicated transducers, and therefore their characteristics are known ( spectrum, intensity, instant of emission ...). See for example:
    L. Ambrozinski, P. Packo, L. Pieczonka, T. Stepinski, T. Uhl, WJ Staszewski "Identification of material properties - efficient modeling approach based on guided wave propagation and spatial multiple signal classification" Structural Control and Health Monitoring, 22 ( 7): 969-983, 2015.
    Mr. Calomfirescu. "Lamb Waves for Structural Health Monitoring in Viscoelastic Composite Materials". doctoral thesis, University of Bremen, 2008.
    In the context of integrated health monitoring, this approach has the disadvantage that the emission of waves requires injecting energy into the environment. This is costly and generally constitutes the dimensioning parameter, in particular because of the strong impact on the on-board mass of the battery supplying the integrated control system.
    To overcome this limitation of active approaches, it has been proposed to use passive methods, exploiting the ambient noise naturally present in the structure, induced by external mechanical stresses (aerodynamic turbulence, engine vibrations, etc.). The system's energy requirement is thus greatly reduced. The electronic system is also simplified because it no longer requires a transmitting function, but only a receiving function.
    For example, the document WO 2015/082292 describes a method of ultrasound tomography exploiting the diffuse noise inside a structure. The disadvantage of this approach is that it requires a large number of sensors - which increases its cost - and complex processing of the acquired data.
    The article by Eric Larose, Philippe Roux, Michel Campillo "Reconstruction of Rayleigh-Lamb dispersion spectrum based on noise obtained from an air-jet forcing", J. Acoust. Soc. Am. 12 (6), December 2007, describes a method of reconstructing an elastic wave dispersion curve in a plate or shell type structure from ambient noise. The application to integrated health monitoring is simply mentioned without details being provided. In addition, the reconstruction method used in this article requires the acquisition of a large number of noise measurements achieving a dense mesh of the structure (one hundred acquisitions at as many measurement points spaced 1 cm apart, obtained by moving 16 sensors , for a square plate 1 m side), which makes the method impractical.
    The article by K. G. Sabra et al. "Using cross correlations of turbulent flow-induced ambient vibrations to estimate the structural impulse response. Application to structural health monitoring >>, J. Acoust. Soc. Am. 121 (4), April 2007 describes an integrated health control method comprising the acquisition of ambient noise by two non-co-located sensors, the determination of an impulse response of the structure by correlation of the signals from two sensors and the use of this impulse response to perform a modal analysis of the structure. If it allows to detect structural defects, the method disclosed by this publication does not allow access to the parameters of the materials, and therefore to follow the effects of aging.
    The invention aims to overcome the aforementioned drawbacks of the prior art. More particularly, it aims to provide a process and an integrated health control system making it possible to monitor the aging of a structure in a reliable, simple and economical manner.
    An object of the invention to achieve this goal is an integrated health control method for a structure supporting modes of guided propagation of elastic waves, comprising the following steps:
    a) acquisition of an ambient noise propagating in the structure by means of at least one pair of non-co-located elastic wave sensors;
    b) estimate, from the ambient noise acquired during the stage
    a), of a function representative of an impulse response of the structure for the elastic propagation between the sensors constituting said pair;
    c) extraction of at least one elastic propagation dispersion curve in the structure by time-frequency analysis of the function representative of an impulse response obtained during the step
    b); and
    d) estimation of at least one parameter indicative of a mechanical property of a material constituting the structure from the dispersion curve obtained during step c).
    According to particular embodiments of such a method: The acquisition of the elastic noise can be carried out over a duration at least equal to the time for mixing the structure.
    Said step b) can be implemented by a method chosen from: a correlation calculation of the elastic noise acquired by the sensors of the pair; the passive reverse filter method; and the correlation of correlation coda.
    Said step c) can comprise the calculation of the time of flight, between the sensors of the pair, of a plurality of packets of elastic waves having different central frequencies.
    Said step d) can be implemented by a method chosen from regression with respect to an analytical model of the dispersion curve and the inversion of a numerical model.
    Step d) may include the estimation of at least one modulus of elasticity of a material constituting the structure, or of a function of at least one such module.
    Step d) can be implemented by an iterative method initialized by a value of said parameter at the beginning of the life of the structure.
    Steps a) to d) can be implemented a plurality of times during a period of use of the structure, the method also comprising the following steps:
    e) monitoring the temporal evolution of the parameter estimated during step d); and
    f) triggering of an alert when the monitoring carried out during step e) indicates an aging of the structure approaching a critical level.
    Steps a) to d) can be implemented a plurality of times using respective pairs of non-co-located sensors, each pair of sensors having a different orientation.
    The method can also include a measurement of the temperature of the structure and the use of the result of this measurement during the implementation of step d).
    The method can be implemented passively.
    The ambient noise acquired during step a) can be recorded and transferred to a data processing device remote from the structure, the following steps of the method being implemented in deferred time by said data processing device.
    Said structure can be of beam, tube, plate or shell type.
    Another object of the invention is an integrated health control system of a plate or shell type structure, comprising:
    at least one pair of non-collocated elastic wave sensors allowing the acquisition of an ambient noise propagating in the structure; and a data processing device configured to: receive from said sensors a signal representative of the acquired ambient noise;
    estimate, from the ambient noise acquired during step a), a function representative of an impulse response of the structure for the elastic propagation between the sensors constituting said pair;
    extract at least one dispersion curve of the elastic propagation in the structure by time-frequency analysis of said function representative of an impulse response; and estimate at least one parameter indicative of a mechanical property of a material constituting the structure from said dispersion curve.
    According to particular embodiments of such a system:
    Said elastic wave sensors can be chosen from Bragg grating sensors on optical fiber, micro-electro-mechanical accelerometers and piezoelectric sensors.
    The system can also include a temperature sensor, and said data processing device can also be configured to use a temperature measurement of the structure acquired by said sensor to estimate said parameter indicative of a mechanical property of a material constituting the structure.
    Other characteristics, details and advantages of the invention will emerge on reading the description made with reference to the accompanying drawings given by way of example and which represent, respectively:
    Figure 1, a flow diagram of a method according to an embodiment of the invention;
    Figure 2, an apparatus according to an embodiment of the invention;
    FIG. 3, a trace of acquisition of ambient noise over 0.1 second;
    FIG. 4, the cross-correlation of the ambient noise acquired by two sensors, over 10 seconds;
    Figures 5a and 5b, a time-frequency analysis of a function representative of the impulse response of the structure obtained by cross-correlation and by application of the passive inverse filter method, respectively;
    Figures 6a and 6b, another time-frequency analysis of a function representative of the impulse response of the structure obtained by cross-correlation and by application of the passive inverse filter method, respectively;
    FIGS. 7a and 7b, dispersion curves obtained by cross-correlation and by application of the passive inverse filter method, respectively;
    FIG. 8, a comparison between dispersion curves obtained by methods according to different embodiments of the invention and theoretical curves; and FIG. 9, an arrangement of several sensors according to an embodiment of the invention.
    As illustrated in FIG. 1, a method according to an embodiment of the invention comprises:
    A first step (a) of acquisition of the ambient noise propagating in the structure under control by means of at least two sensors located at different locations.
    A second step (b) of estimating the impulse response (Green's function) - or more generally of a function representative of this impulse response but not necessarily identical to it - from the acquisitions made in the first step.
    A third step (c) of extracting a dispersion curve by time-frequency analysis of the impulse response estimated in the second step.
    A fourth step (d) of estimating a mechanical parameter characterizing the material constituting the structure from this dispersion curve. It can be for example the Young's modulus, more generally a modulus of the tensor of elastic constants (modulus of elasticity), or a function of one or more of these modules.
    Steps (a) to (d) are repeated several times, preferably at regular intervals, during the lifetime of the structure, which makes it possible to monitor the temporal evolution of the mechanical parameter estimated during step (d), and therefore aging of the material considered (step (e)). When this aging approaches a critical level, an alert can be triggered (step (f)). For example, the event triggering the alert may be the decrease in Young's modulus below a certain level.
    In the following, different embodiments of steps (a) to (d) will be described in detail.
    First step: acquisition of ambient noise
    By ambient noise is meant elastic wave field in the structure coming from a multitude of sources, potentially of very low intensities, at random positions and times or from sources in a more limited but more intense number generating multi-diffused waves. in reverberating cavities or diffusing media.
    This ambient noise can be acquired by means of various kinds of sensors known from the prior art: piezoelectric transducers (PZT), microelectromechanical accelerometers (MEMS), Bragg gratings on optical fiber (FBG), etc. The implementation of the invention requires at least two such sensors, integrated into the structure at two different locations. For the sake of simplicity, we will seek to minimize the number of sensors, therefore to use only a pair of them whenever possible. In certain cases, however, it will be necessary to use several sensors, in particular if one wants to follow the aging at the level of several zones of the structure or if one works on an anisotropic composite which one wants to characterize according to several directions. This latter situation is illustrated in FIG. 9, where four sensors C0, C1, C2, C3 form three pairs (C0, C1), (CO, C2), (CO, C3) which make it possible to characterize the structure in three directions d1 , d2, d3. Of course, it is possible to use even more sensors to characterize the structure along a larger number of directions. It is also possible to use the four sensors to characterize the structure in three additional directions, by considering the pairs (C1, C2), (C1, C3) and / or (C2, C3).
    The acquisition is completely passive, it requires little energy, so a system according to the invention can be easily embarked on an airplane, a boat or at the bottom of the sea. This passive measurement is compatible with the use of transducers operating in reception mode only, such as the above-mentioned FBGs. This FBG option is particularly interesting when it is desired to equip the structure with a number of measurement points greater than two, for example to monitor the aging of several zones of the structure. Indeed, while the use of PZTs requires two electrical wires per sensor, a single optical fiber - for example integrated between the plies of a composite material - can include dozens of measurement points. The number of entry points into the structure is therefore very limited, which further limits potential weakening points.
    The method is all the more effective since the elastic field is diffuse. Geometric elements diffracting multiple times the elastic waves are therefore not annoying, on the contrary, they improve the relevance of the method. This is particularly true in industrial structures which are never simple plates but comprise stiffeners, rivets, local extra thicknesses ... The convergence of the method is facilitated when the condition of equi-distribution of energy is satisfied , that is to say when the phase and amplitude distribution of the waves is random, and therefore the latter propagates homogeneously in all directions. This condition is notably satisfied (sufficient condition but not necessary) when the acquisition of the signals is carried out over a duration at least equal to the time for mixing the structure. The mixing time is ίο defined as the time necessary for an elastic wave to give rise to a diffuse field, with no preferred direction of propagation.
    Figure 2 illustrates an integrated health control system according to an embodiment of the invention, which has been used for demonstration purposes. Structure S consists of a 2 mm thick aluminum plate, to which have been attached two piezoelectric transducers CA, CB used as sensors, located at points A and B arranged on the surface of the structure and spaced 600 mm. The ambient noise was created by using a mobile nozzle BM, displaced in a pseudo-random manner, to direct a jet of compressed air JAC on the plate. It was acquired by the transducers for a time of 10 seconds; Figure 3 shows the signal acquired by the AC transducer for 0.1 seconds.
    Natural noise sources in industrial structures can be, for example, the turbulent boundary layer in aeronautics, the impact of waves, the vibrations induced by engines or a turbulent flow in a tube (penstocks).
    The ultrasonic field picked up by the transducers is transmitted to a DTD data processing device. The latter generally includes electronics for conditioning (amplification, filtering) and converting signals from the sensors to digital format, as well as a digital processor which implements the following steps - (b) to (d), or ( b) to (f) of the process. The digital processor may be a computer or a microprocessor card equipped with a memory storing an appropriate program, or else a dedicated digital circuit, produced from a programmable device such as an FPGA. The data processing device can consist of two separate parts, one associated with the structure and the other remote. In the case, for example, where the structure to be monitored is an element of an aircraft, the on-board part can store the signals, the processing being carried out by a computer on the ground after landing. Or the on-board party can transmit the signals to the ground via a radio link, which allows processing in real time if necessary. Yet another option consists in carrying out the processing in the on-board part of the system and in transmitting (or storing locally) only the results, that is to say the identified material parameters.
    A temperature sensor (reference CT in Figure 2) can optionally be provided to precisely calibrate the distance between the sensors, if it is not well known, or to compensate for the effects of temperature on the propagation of waves .
    Indeed, a method according to the invention requires knowing with great precision the position of the sensors. An alternative to measuring the individual positions of these sensors is a calibration carried out immediately after installation, at a controlled temperature, in order to measure the flight times between the sensors. By knowing the speed of the initial state at t 0 we can deduce the position of the sensors with very good accuracy. If the speed of the initial state is not precisely known, we can store the flight time for each pair of sensors and work on a variation in flight time.
    Knowing the temperature at the time of calibration, if we know the temperature of the structure using a thermocouple integrated at time t, we can also compensate for the variation in flight time induced by temperature ( one can think of the great variations in temperature during the flight of an airplane).
    Second step: estimation of the impulse response (Green's function)
    Several methods known in the prior art make it possible to determine the Green's function of the structure - defining its impulse response - from measurements of ambient noise. A preferred embodiment of the invention uses the correlation of diffuse elastic fields, described in the article by R.L. Weaver and 0.1. Lobkis "Ultrasonics without a source: Thermal fluctuation correlations at MHz frequencies >> Physical Review Letters, 87: 134301,2001.
    This method provides for calculating a cross-correlation of the elastic fields ua and ub (displacement fields) acquired simultaneously by the sensors CA and CB:
    Γαβ (0 = fu A (t + τ) .ιι Β (τ) άτ.
    Figure 3 is a portion of a trace of a noise acquired in the system of Figure 2, and Figure 4 is a graph of a cross-correlation obtained from such noise, measured at two different locations.
    When the phase and amplitude distribution of the elastic waves is random (condition of equi-distribution of the energy), which is generally verified if the structure is diffusing and if the noise is acquired over a sufficient duration (greater or equal mixing time), there is a link between this cross correlation and the causal (Gab (î)) and anti10 causal (Gba (-t)) Green functions between points A and B:
    “F (t) ® [G AB (t) - G BA (-t)] where F is a filter which takes into account the bandwidth of the sensors and the spectrum of ambient noise present in the structure.
    As a reminder, Green's function between A and B is the recording that we would obtain in B if a source emitted an impulsive signal at A (we therefore speak of an impulse response from the medium).
    It is also possible not to calculate the derivative, and for example to directly use the cross correlation as a function representative of the impulse response. Indeed, the aim of this step is not to determine Green's function as such, but to characterize the
    0 impulse response to then be able (step (b)) to extract dispersion curves from it.
    To find exactly the causal and anti-causal Green functions between A and B, the transducers should have a constant frequency response and the ambient noise should be white noise. In practice
    5 these conditions will never be checked exactly, but may be checked in an approximate and sufficient way to achieve the aims of the invention.
    Experience shows that satisfactory results can be obtained for transducers having a bandwidth between 1 kHz (or a few kHz) and a few MHz, for example 10 MHz.
    Other methods can be used if the condition of equal energy distribution is not satisfied. Two of them will be mentioned in particular:
    the passive reverse filter, described in the article by T. Gallot et al. "A passive inverse filter for Green's function retrieval", J. Acoust. Soc. Am. 131 (1), January 2012;
    the correlation of correlation coda, described in the article by L. Sthely at al. "Reconstructing Green's function by correlation of the coda of the correlation (C 3 ) of ambient seismic noise", Journal Of Geophysical Research, Vol. 113, B11306, (2008). The latter technique requires at least three sensors.
    Third step: extraction of a dispersion curve The guided elastic waves which can propagate in mechanical guiding structures (beams; plates or shells, supporting so-called Lamb modes; massive objects whose surfaces support Rayleigh waves) are in general dispersive: the propagation speed depends on the frequency. Each guided propagation mode can be characterized by curves - known as dispersion curves - representing different characteristics of the mode (wave number, phase speed, group speed, wavelength, or even attenuation) as a function of frequency. In the following we will mainly consider the group speed, but this should not be considered limiting. These dispersion curves can be estimated from knowledge of the impulse response, obtained during the previous step, using time-frequency analysis techniques. The advantage of the dispersion curves for the integrated health control is that they depend directly on the parameters of the material of the plate. In the case of a homogeneous isotropic material, these parameters can be expressed by the Young's modulus and / or the Poisson's ratio, which are conventionally used in mechanics to study the behavior of the material. More generally, it can be one or more modules of the tensor of the elastic constants of the material, or functions of these modules.
    The simplest technique for obtaining a dispersion curve consists in filtering the impulse response of the structure by bandpass filters having different central frequencies. In this way, several packets of waves are obtained at different times, linked to their group speeds. This is illustrated in Figures 5A and 5B; FIG. 5A was obtained by calculating the cross correlation of the noise; FIG. 5B by the technique of the inverse filter; the noise acquired is the same in both cases and was obtained by the system of FIG. 2).
    These figures show the presence of two modes, a low dispersive So mode, at high frequency, and a more dispersive A o mode, at low frequency. Markers, in the form of a square for the A o mode and a circle for the S o mode, identify the theoretical flight times of the wave packets; it can be checked that they coincide, with a very good approximation, with the peaks of the wave packets calculated in accordance with the invention. In the following, only the A o mode is considered.
    By identifying the time corresponding to the maximum of each wave packet, the flight time of the packet is determined over the distance A - B and therefore, the distance being assumed to be known, the group speed at the center frequency of the packet.
    The appearance of the S o mode around 120 kHz creates a rebound at the edge of the plate of this mode which comes to interfere with A o (So propagates about twice as fast as A 0 for these frequencies). We cannot therefore take advantage of flight times above 120kHz in this configuration. In practice, this problem can be avoided by placing the sensors far from the reflecting edges.
    Other time-frequency analysis techniques can be used, for example reallocated spectrograms, reallocated scalograms, the "Hilbert-Huang Transform", the "SyncroSqueezing Transform", etc ...
    For example, the "SyncroSqueezing Transform" and the method of reallocated spectrograms are described in the article by F. Auger,
    P. Flandrin, Y.-T. Lin, S. Mclaughlin, S. Meignen, T. Oberlin, H.-T. Wu, "Time3060743
    Frequency Reassignment and Synchrosqueezing: An overview ", IEEE Signal Processing Magazine, vol. 30, no. 6, pp. 32-41, November 2013.
    Figures 6A and 6B illustrate reallocated spectrograms, containing the same information as the graphs of Figures 5A and 5B.
    FIGS. 7A and 7B show the evolution of the group speeds by identification of the flight times on the passive signals acquired by the system of FIG. 2 for the case of the derivative of the correlation of diffuse elastic fields (7A) and for that of the passive reverse filter (7B). In these figures, the points represent the calculated values and the lines the theoretical dispersion curves. We can see that the experimental results are in good agreement with the theory, which proves the feasibility of the identification of the mechanical characteristics by passive methods.
    Fourth step: estimation of a mechanical parameter characterizing the material constituting the structure
    This fourth step can be implemented by minimizing the difference between the dispersion curves reconstructed experimentally and those obtained by a theoretical, analytical or numerical model. This minimization gives access to the properties of the material of the structure. We therefore proceed either by minimization with respect to an analytical equation, when it is known, or by inversion of a numerical model of the calculation of the indicators.
    When we try to follow the aging of a material, we know its mechanical properties at an instant t 0 taken as being the beginning of its life. This knowledge makes it possible to initialize the minimization method, implemented iteratively. This initialization will necessarily be very close to the result, avoiding any risk of convergence towards a local minimum. During the lifetime of the material, the estimated parameter will change as a function of the aging of the material.
    As an example we consider experimental data on the band [20; 110] kHz acquired on an aluminum plate 2 mm thick (see fig. 2). The curve in dotted lines in FIG. 8 shows the dispersion curve of the theoretical group speed of mode A o , for a structure at the start of life; the dashed curve was obtained by reducing the Young's modulus of the material by 25%, so as to simulate the effects of aging. These curves were calculated using a semianalytic finite element method ("SAFE") described in the article by I. Bartoli et al.
    "Modeling wave propagation in damped waveguides of arbitrary crosssection", Journal of Sound and Vibration 295, pp. 685-707 (2006).
    Still in FIG. 8, the gray dots correspond to the values of the group speed calculated, from the experimental data, by cross correlation; black stars, at values calculated by the passive inverse filter method. The solid gray and black lines, respectively, are the curves calculated by regression using Mindlin-Reissner theory. This theory provides an analytical expression of the group speed as a function of two parameters: the plate speed V P and the shear speed modified by Mindlin's theory V T '. The plate speed V P is the group speed of the mode S o at the zero frequency, and is i — v given by = I - 7, where V | _ is the phase speed of the waves h.
    longitudinal and V T that of transverse waves, or shear. The values of these parameters are chosen so as to minimize the mean square deviation with the group speed values obtained from the
    0 experimental results (gray dots and black stars).
    Once the values V P and V ' T have been determined, the Young's modulus E and the fish coefficient v can be calculated using the following relationships:
    n V t
    Î2p ^ n 2 V P
    48v T n 2 V P 2
    48u, 2 n 2 V P
    48ν τ n 2 V P
    48V T
    Table 1 shows the theoretical values of V p , V't, E and v, and those determined by the correlation derivative method and the passive inverse filter. The percentages of errors compared to the theoretical values (2024 aluminum plate 2 mm thick) are entirely acceptable.
    Theory (m / s) Correlation (m / s) Passive reverse filter (m / s) Plate speed 5461 5286 (3.2% error) 5470 (0.2% error) Shear speed (Mindlin) 2848 2816 (1.1% error) 2812 (1.3% error) Younq module (GPa) 71.3 68.2 (4.3% error) 70.5 (3.2% error) Poisson coefficient 0.34 0.31 (8.8% error) 0.36 (5.9% error) Table 1
    Table 2 shows the effect of an aging which corresponds to a 25% reduction in the Young's modulus, which is conventionally used in the literature. We therefore go from a healthy state where E = 71.3 GPa to a damaged state where E = 53.5 GPa. The system is therefore sensitive enough to detect such variations and therefore anticipate the aging of the material before it is critical.
    100% Young's modulus 75% Young's modulus Plate speed 5461 4733 (13.3% change) Shear speed (Mindlin) 2848 2466 (13.4% change)
    Table 2
    0 This step can use techniques to identify parameters different from a simple regression, for example artificial neural networks. See for example E. Pabisek and Z. Waszczyszyn, “Identification of thin elastic isotropie plate parameters applying Guided Wave Measurement and Artificial Neural Networks” Mechanical Systems and Signal Processing, 2015
    The technique described so far takes advantage of the natural sources of noise present in the structure. Nothing prevents, in certain cases, from adding active noise sources, for example PZT placed in the structure, in order to be able to make measurements even in the absence of noise (for example, in an airplane if the natural sources are the turbulences in flight, one can also use the active sources to be able to make a measurement on the ground, when there is more noise in the structure). These sources do not need to be synchronized with the receivers which simplifies the electronic assembly compared to the active methods.
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1. A method of integrated health control of a structure (S) supporting modes of guided propagation of elastic waves, comprising the following steps:
    a) acquisition of an ambient noise propagating in the structure by means of at least one pair of non-co-located elastic wave sensors (CA, CB);
    b) estimate, from the ambient noise acquired during the stage
    a), of a function representative of an impulse response of the structure for the elastic propagation between the sensors constituting said pair;
    c) extraction of at least one elastic propagation dispersion curve in the structure by time-frequency analysis of the function representative of an impulse response obtained during the step
    b); and
    d) estimation of at least one parameter indicative of a mechanical property of a material constituting the structure from the dispersion curve obtained during step c).
    [2" id="c-fr-0002]
    2. Method according to claim 1 in which the acquisition of the elastic noise is carried out over a duration at least equal to the time of mixing of the structure.
    [3" id="c-fr-0003]
    3. Method according to one of the preceding claims in which said step b) is implemented by a method chosen from:
    a correlation calculation of the elastic noise acquired by the sensors of the pair;
    the passive reverse filter method; and the correlation of correlation coda.
    [4" id="c-fr-0004]
    4. Method according to one of the preceding claims, in which said step c) comprises the calculation of the time of flight, between the sensors of the pair, of a plurality of elastic wave packets having different central frequencies.
    [5" id="c-fr-0005]
    5. Method according to one of the preceding claims, in which said step d) is implemented by a method chosen from regression with respect to an analytical model of the dispersion curve and the inversion of a digital model.
    [6" id="c-fr-0006]
    6. Method according to one of the preceding claims wherein step d) comprises the estimation of at least one modulus of elasticity of a material constituting the structure, or of a function of at least one such module.
    [7" id="c-fr-0007]
    7. Method according to one of the preceding claims in which step d) is implemented by an iterative method initialized by a value of said parameter at the start of the life of the structure.
    [8" id="c-fr-0008]
    8. Method according to one of the preceding claims, in which steps a) to d) are implemented a plurality of times during a period of use of the structure, the method also comprising the following steps:
    e) monitoring the temporal evolution of the parameter estimated during step d); and
    f) triggering of an alert when the monitoring carried out during step e) indicates an aging of the structure approaching a critical level.
    [9" id="c-fr-0009]
    9. Method according to one of the preceding claims, in which steps a) to d) are implemented a plurality of times using respective pairs of non-co-located sensors (C0, C1; C0, C2; C0, C3 ), each pair of sensors having a different orientation (d1, d2, d3).
    [10" id="c-fr-0010]
    10. Method according to one of the preceding claims also comprising a measurement of the temperature of the structure and the use of the result of this measurement during the implementation of step d).
    [11" id="c-fr-0011]
    11. Method according to one of the preceding claims, implemented passively.
    [12" id="c-fr-0012]
    12. Method according to one of the preceding claims, in which the ambient noise acquired during step a) is recorded and transferred to a data processing device remote from the structure, the following steps of the method being implemented in time. deferred by said data processing device.
    [13" id="c-fr-0013]
    13. Method according to one of the preceding claims wherein said structure is of beam, tube, plate or shell type.
    [14" id="c-fr-0014]
    14. Integrated health control system for a plate or shell type structure (S), comprising:
    at least one pair of non-co-located elastic wave sensors (CA, CB) allowing the acquisition of an ambient noise propagating in the structure; and a data processing device (DTD) configured to:
    receiving from said sensors a signal representative of the acquired ambient noise;
    estimate, from the ambient noise acquired during step a), a function representative of an impulse response of the structure for the elastic propagation between the sensors constituting said pair;
    extract at least one dispersion curve of the elastic propagation in the structure by time-frequency analysis of said function representative of an impulse response; and estimate at least one parameter indicative of a mechanical property of a material constituting the structure from said dispersion curve.
    15. The system as claimed in claim 14, in which said elastic wave sensors are chosen from Bragg grating sensors on optical fiber, micro-electro-mechanical accelerometers and piezoelectric sensors.
    16. System according to one of claims 14 or 15 also comprising a temperature sensor (CT) and in which said data processing device is also configured to use a temperature measurement of the structure acquired by said sensor to estimate said parameter indicative of a mechanical property of a material constituting
    [15" id="c-fr-0015]
    15 the structure.
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    同族专利:
    公开号 | 公开日
    WO2018109159A1|2018-06-21|
    FR3060743B1|2019-05-17|
    EP3555585A1|2019-10-23|
    US20190317056A1|2019-10-17|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    EP2728348A2|2012-10-31|2014-05-07|The Boeing Company|Apparatus and a method for measuring in-plane elastic constants for a laminate|
    WO2015119498A1|2014-02-05|2015-08-13|Nederlandse Organisatie Voor Toegepast-Natuurwetenschappelijk Onderzoek Tno|System and method for crack monitoring|FR3073289A1|2017-11-08|2019-05-10|Commissariat A L'energie Atomique Et Aux Energies Alternatives|HEALTH CONTROL OF AN INDUSTRIAL STRUCTURE|
    WO2020025390A1|2018-08-01|2020-02-06|Commissariat A L'energie Atomique Et Aux Energies Alternatives|Inspection of rail health|
    WO2021152243A1|2020-01-29|2021-08-05|Safran Aircraft Engines|Aircraft turbomachine casing and method of manufacturing same|US8290719B2|2008-09-26|2012-10-16|The Boeing Company|Mode identification and decomposition for ultrasonic signals|
    FR3014200B1|2013-12-02|2017-05-26|Commissariat Energie Atomique|CONTROL OF INDUSTRIAL STRUCTURE|FR3105148A1|2019-12-23|2021-06-25|Commissariat A L'energie Atomique Et Aux Energies Alternatives|SYSTEM AND METHOD FOR DETECTION OF A FAULT IN A RAIL OF A RAILWAY|
    法律状态:
    2018-01-02| PLFP| Fee payment|Year of fee payment: 2 |
    2018-06-22| PLSC| Publication of the preliminary search report|Effective date: 20180622 |
    2019-12-31| PLFP| Fee payment|Year of fee payment: 4 |
    2020-12-28| PLFP| Fee payment|Year of fee payment: 5 |
    2021-12-31| PLFP| Fee payment|Year of fee payment: 6 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1662485|2016-12-15|
    FR1662485A|FR3060743B1|2016-12-15|2016-12-15|METHOD AND SYSTEM FOR INTEGRATED HEALTH CONTROL OF A MECHANICAL STRUCTURE BY DIFFUSED ELASTIC WAVES|FR1662485A| FR3060743B1|2016-12-15|2016-12-15|METHOD AND SYSTEM FOR INTEGRATED HEALTH CONTROL OF A MECHANICAL STRUCTURE BY DIFFUSED ELASTIC WAVES|
    US16/469,625| US20190317056A1|2016-12-15|2017-12-15|Method and system for controlling the integrated health of a mechanical structure by diffuse elastic waves|
    EP17828875.9A| EP3555585A1|2016-12-15|2017-12-15|Method and system for controlling the integrated health of a mechanical structure by diffuse elastic waves|
    PCT/EP2017/083000| WO2018109159A1|2016-12-15|2017-12-15|Method and system for controlling the integrated health of a mechanical structure by diffuse elastic waves|
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