SAM
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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Sun, 31 May 2020 16:32:54 GMT2020-05-31T16:32:54ZVerification and Validation of Structural Health Monitoring Algorithms: A Maturation Procedure
http://hdl.handle.net/10985/10040
Verification and Validation of Structural Health Monitoring Algorithms: A Maturation Procedure
HMAD, Ouadie; FENDZI, Claude; MECHBAL, Nazih; REBILLAT, Marc
Structural Health Monitoring (SHM) system offers new approaches to interrogate the integrity of structures. However, their reliability has still to be demonstrated an quantified to enable confidence transition from R&D to field implementation. In general, SHM algorithms performances are illustrated by topography study but it is not sufficient in a reliability assessment context. In the sense, that there is no quantification of the performance. To address this key issue, a dedicated maturation procedure is proposed in this paper. It is strongly inspired from the six sigma procedure for processes improvement to gradually improve SHM algorithms in order to reach the required maturity level. This paper presents the application of this procedure to a damage SHM localization algorithm as case study. To address this issue, finite element models and experimentation on the monitored structure have been used. It is concluded with a need of a new specific SHM algorithm intrinsic maturity scale. These maturity scales can be defined with respect to the functions of the considered SHM algorithm and the type of the used data.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/100402015-01-01T00:00:00ZHMAD, OuadieFENDZI, ClaudeMECHBAL, NazihREBILLAT, MarcStructural Health Monitoring (SHM) system offers new approaches to interrogate the integrity of structures. However, their reliability has still to be demonstrated an quantified to enable confidence transition from R&D to field implementation. In general, SHM algorithms performances are illustrated by topography study but it is not sufficient in a reliability assessment context. In the sense, that there is no quantification of the performance. To address this key issue, a dedicated maturation procedure is proposed in this paper. It is strongly inspired from the six sigma procedure for processes improvement to gradually improve SHM algorithms in order to reach the required maturity level. This paper presents the application of this procedure to a damage SHM localization algorithm as case study. To address this issue, finite element models and experimentation on the monitored structure have been used. It is concluded with a need of a new specific SHM algorithm intrinsic maturity scale. These maturity scales can be defined with respect to the functions of the considered SHM algorithm and the type of the used data.Vibroacoustics of the piano soundboard : (Non)linearity and modal properties in the low- and mid-frequency ranges
http://hdl.handle.net/10985/8195
Vibroacoustics of the piano soundboard : (Non)linearity and modal properties in the low- and mid-frequency ranges
EGE, Kerem; BOUTILLON, Xavier; REBILLAT, Marc
The piano soundboard transforms the string vibration into sound and therefore, its vibrations are of primary importance for the sound characteristics of the instrument. An original vibro-acoustical method is presented to isolate the soundboard nonlinearity from that of the exciting device (here: a loudspeaker) and to measure it. The nonlinear part of the soundboard response to an external excitation is quantitatively estimated for the ﬁrst time, at 40 dB below the linear part at the ff nuance. Given this essentially linear response, a modal identiﬁcation is performed up to 3 kHz by means of a novel high resolution modal analysis technique [K. Ege, X. Boutillon, B. David, High-resolution modal analysis, Journal of Sound and Vibration 325 (4–5) (2009) 852–869]. Modal dampings (which, so far, were unknown for the piano in this frequency range) are determined in the mid-frequency domain where FFT-based methods fail to evaluate them with an acceptable precision. They turn out to be close to those imposed by wood. A ﬁnite-element modelling of the soundboard is also presented. The low-order modal shapes and the comparison between the corresponding experimental and numerical modal frequencies suggest that the boundary conditions can be considered as blocked, except at very low frequencies. The frequency-dependency of the estimated modal densities and the observation of modal shapes reveal two well-separated regimes. Below 1 kHz, the soundboard vibrates more or less like a homogeneous plate. Above that limit, the structural waves are conﬁned by ribs, as already noticed by several authors, and localised in restricted areas (one or a few inter-rib spaces), presumably due to a slightly irregular spacing of the ribs across the soundboard.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/81952013-01-01T00:00:00ZEGE, KeremBOUTILLON, XavierREBILLAT, MarcThe piano soundboard transforms the string vibration into sound and therefore, its vibrations are of primary importance for the sound characteristics of the instrument. An original vibro-acoustical method is presented to isolate the soundboard nonlinearity from that of the exciting device (here: a loudspeaker) and to measure it. The nonlinear part of the soundboard response to an external excitation is quantitatively estimated for the ﬁrst time, at 40 dB below the linear part at the ff nuance. Given this essentially linear response, a modal identiﬁcation is performed up to 3 kHz by means of a novel high resolution modal analysis technique [K. Ege, X. Boutillon, B. David, High-resolution modal analysis, Journal of Sound and Vibration 325 (4–5) (2009) 852–869]. Modal dampings (which, so far, were unknown for the piano in this frequency range) are determined in the mid-frequency domain where FFT-based methods fail to evaluate them with an acceptable precision. They turn out to be close to those imposed by wood. A ﬁnite-element modelling of the soundboard is also presented. The low-order modal shapes and the comparison between the corresponding experimental and numerical modal frequencies suggest that the boundary conditions can be considered as blocked, except at very low frequencies. The frequency-dependency of the estimated modal densities and the observation of modal shapes reveal two well-separated regimes. Below 1 kHz, the soundboard vibrates more or less like a homogeneous plate. Above that limit, the structural waves are conﬁned by ribs, as already noticed by several authors, and localised in restricted areas (one or a few inter-rib spaces), presumably due to a slightly irregular spacing of the ribs across the soundboard.A Probabilistic Multi-class Classifier for Structural Health Monitoring
http://hdl.handle.net/10985/9287
A Probabilistic Multi-class Classifier for Structural Health Monitoring
MECHBAL, Nazih; URIBE, Juan Sebastian; REBILLAT, Marc
In this paper, a probabilistic multi-class pattern recognition algorithm is developed for damage detection, localization, and quantification in smart mechanical structures. As these structures can face damages of different severities located at various positions, multi-class classifiers are naturally needed in that context. Furthermore, because of the lack of available data in the damaged state and of environmental effects, the experimentally obtained damage sensitive features may differ from those learned offline by the classifier. A multiclass classifier that provides probabilities associated with each damage severity and location instead of a binary decision is thus greatly desirable in that context. To tackle this issue, we propose an original support vector machine (SVM) multi-class clustering algorithm that is based on a probabilistic decision tree (PDT) and that produces a posteriori probabilities associated with damage existence, location, and severity. Furthermore, the PDT is here built by iteratively subdividing the surface of the structure and thus takes into account the actual structure geometry. The proposed algorithm is very appealing as it combines both the computational efficiency of tree architectures and the classification accuracy of SVMs. The effectiveness of this algorithm is illustrated experimentally on a composite plate instrumented with piezoelectric elements on which damages are simulated using added masses. Damage sensitive features are computed using an active approach based on the permanent emission of non-resonant Lamb waves into the structure and on the recognition of amplitude disturbed diffraction patterns. On the basis of these damage-sensitive features, the proposed multi-class probabilistic classifier generates decisions that are in excellent agreement with the actual severities and locations of the simulated damages.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/92872015-01-01T00:00:00ZMECHBAL, NazihURIBE, Juan SebastianREBILLAT, MarcIn this paper, a probabilistic multi-class pattern recognition algorithm is developed for damage detection, localization, and quantification in smart mechanical structures. As these structures can face damages of different severities located at various positions, multi-class classifiers are naturally needed in that context. Furthermore, because of the lack of available data in the damaged state and of environmental effects, the experimentally obtained damage sensitive features may differ from those learned offline by the classifier. A multiclass classifier that provides probabilities associated with each damage severity and location instead of a binary decision is thus greatly desirable in that context. To tackle this issue, we propose an original support vector machine (SVM) multi-class clustering algorithm that is based on a probabilistic decision tree (PDT) and that produces a posteriori probabilities associated with damage existence, location, and severity. Furthermore, the PDT is here built by iteratively subdividing the surface of the structure and thus takes into account the actual structure geometry. The proposed algorithm is very appealing as it combines both the computational efficiency of tree architectures and the classification accuracy of SVMs. The effectiveness of this algorithm is illustrated experimentally on a composite plate instrumented with piezoelectric elements on which damages are simulated using added masses. Damage sensitive features are computed using an active approach based on the permanent emission of non-resonant Lamb waves into the structure and on the recognition of amplitude disturbed diffraction patterns. On the basis of these damage-sensitive features, the proposed multi-class probabilistic classifier generates decisions that are in excellent agreement with the actual severities and locations of the simulated damages.Laser shock a novel way to generate calibrated delamination in composites: concept and first results
http://hdl.handle.net/10985/12394
Laser shock a novel way to generate calibrated delamination in composites: concept and first results
GHRIB, Meriem; BERTHE, Laurent; REBILLAT, Marc; MECHBAL, Nazih; GUSKOV, Mikhail; ECAULT, Romain
Structural Health Monitoring (SHM) has been gaining importance in recent years. SHM aims at providing structures with similar functionality as the biological nervous system and it is organized into four main steps: detection, localization, assessment, and prognosis. This paper considers SHM assessment level and more particularly the estimation of the severity of delamination-type damage in Carbon Fiber Reinforced Polymer (CFRP) laminates. Prior to quantification algorithms implementation, it is critical to properly prepare the supports on which algorithms will be tested. Teflon inserts and conventional drop tower impacts are commonly used techniques in the SHM community to generate or simulate delaminations. However with such techniques it is difficult to generate controlled delaminationtype damage in a realistic manner. Conventional impacts do not necessarily induce uniquely delamination-type damage. Teflon inserts still remain very far from representing a realistic delamination. In the present paper we investigate Laser Shock Wave Technique (LSWT), a new way to generate controlled delaminations in composites. In particular, the symmetrical laser shock approach was applied to CFRP laminates in order to generate delamination-type damage in a calibrated and realistic way. A particular attention was paid to the effect of time delay and laser beams energies on damage position and severity respectively. Post-mortem analyses were performed to characterize the induced damage. Results show a high potential of LSWT for damage calibration in both size and location.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/123942015-01-01T00:00:00ZGHRIB, MeriemBERTHE, LaurentREBILLAT, MarcMECHBAL, NazihGUSKOV, MikhailECAULT, RomainStructural Health Monitoring (SHM) has been gaining importance in recent years. SHM aims at providing structures with similar functionality as the biological nervous system and it is organized into four main steps: detection, localization, assessment, and prognosis. This paper considers SHM assessment level and more particularly the estimation of the severity of delamination-type damage in Carbon Fiber Reinforced Polymer (CFRP) laminates. Prior to quantification algorithms implementation, it is critical to properly prepare the supports on which algorithms will be tested. Teflon inserts and conventional drop tower impacts are commonly used techniques in the SHM community to generate or simulate delaminations. However with such techniques it is difficult to generate controlled delaminationtype damage in a realistic manner. Conventional impacts do not necessarily induce uniquely delamination-type damage. Teflon inserts still remain very far from representing a realistic delamination. In the present paper we investigate Laser Shock Wave Technique (LSWT), a new way to generate controlled delaminations in composites. In particular, the symmetrical laser shock approach was applied to CFRP laminates in order to generate delamination-type damage in a calibrated and realistic way. A particular attention was paid to the effect of time delay and laser beams energies on damage position and severity respectively. Post-mortem analyses were performed to characterize the induced damage. Results show a high potential of LSWT for damage calibration in both size and location.Exponential sine sweeps for the autonomous estimation of nonlinearities and errors assessment by bootstrap Application to thin vibrating structures
http://hdl.handle.net/10985/10369
Exponential sine sweeps for the autonomous estimation of nonlinearities and errors assessment by bootstrap Application to thin vibrating structures
REBILLAT, Marc; EGE, Kerem; GALLO, Maxime; ANTONI, Jérôme
Vibrating structures are generally assumed to behave linearly and in a noise-free environment. This is in practice not perfectly the case. First, nonlinear phenomena such as jump phenomenon, hysteresis or internal resonance appear when the transverse vibration of a bi-dimensional structure exceeds amplitudes in the order of magnitude of its thickness. Secondly, the presence of plant noise is a natural phenomenon that is unavoidable for all experimental measurements. In order to perform reliable measurements of vibrating mechanical structures one should thus keep in mind these two issues and care about them. However, it turns out that they are actually coupled. Indeed, all the noise that is not correctly removed from the measurements could be misinterpreted as nonlinearities, thus polluting measurements. And if nonlinearities are not accurately estimated, they will end up within the noise signal and information about the structure under study will be lost. We thus try here to solve simultaneously both issues. The underlying idea consists in extracting the maximum of available linear and nonlinear deterministic information from measurements without misinterpreting noise. The aim of this talk is thus to provide a methodology that allows for the autonomous estimation of nonlinearities and errors assessment by bootstrap on a given vibrating structure. Nonlinearities are estimated by means of a block-oriented nonlinear model approach based on parallel Hammerstein models and on exponential sine sweeps. Estimation errors are simultaneously assessed using repetitions of the input signal (multi exponential sine sweeps) as the input of a bootstrap procedure. Mathematical foundations and practical implementation of the method are discussed on an experimental example. The experiment chosen here consists in exciting a steel plate under various boundary conditions with exponential sine sweeps and at different levels, in order to assess the evolutions of nonlinearities and of signal to noise ratio over a wide range of frequencies and input amplitudes.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/103692015-01-01T00:00:00ZREBILLAT, MarcEGE, KeremGALLO, MaximeANTONI, JérômeVibrating structures are generally assumed to behave linearly and in a noise-free environment. This is in practice not perfectly the case. First, nonlinear phenomena such as jump phenomenon, hysteresis or internal resonance appear when the transverse vibration of a bi-dimensional structure exceeds amplitudes in the order of magnitude of its thickness. Secondly, the presence of plant noise is a natural phenomenon that is unavoidable for all experimental measurements. In order to perform reliable measurements of vibrating mechanical structures one should thus keep in mind these two issues and care about them. However, it turns out that they are actually coupled. Indeed, all the noise that is not correctly removed from the measurements could be misinterpreted as nonlinearities, thus polluting measurements. And if nonlinearities are not accurately estimated, they will end up within the noise signal and information about the structure under study will be lost. We thus try here to solve simultaneously both issues. The underlying idea consists in extracting the maximum of available linear and nonlinear deterministic information from measurements without misinterpreting noise. The aim of this talk is thus to provide a methodology that allows for the autonomous estimation of nonlinearities and errors assessment by bootstrap on a given vibrating structure. Nonlinearities are estimated by means of a block-oriented nonlinear model approach based on parallel Hammerstein models and on exponential sine sweeps. Estimation errors are simultaneously assessed using repetitions of the input signal (multi exponential sine sweeps) as the input of a bootstrap procedure. Mathematical foundations and practical implementation of the method are discussed on an experimental example. The experiment chosen here consists in exciting a steel plate under various boundary conditions with exponential sine sweeps and at different levels, in order to assess the evolutions of nonlinearities and of signal to noise ratio over a wide range of frequencies and input amplitudes.Repeated exponential sine sweeps for the autonomous estimation of nonlinearities and bootstrap assessment of uncertainties
http://hdl.handle.net/10985/10780
Repeated exponential sine sweeps for the autonomous estimation of nonlinearities and bootstrap assessment of uncertainties
REBILLAT, Marc; EGE, Kerem; MECHBAL, Nazih; ANTONI, Jérôme
Systems and structures are generally assumed to behave linearly and in a noise-free environment. This is in practice not perfectly the case. First, nonlinear phenomena can appear and second, the presence of noise is unavoidable for all experimental measurements. Nonlinearities can be considered as a deterministic process in the sense that in the absence of noise the output signal depends only on the input signal. Noise is purely stochastic: in the absence of an input signal, the output signal is not null and cannot be predicted at any arbitrary instant. It turns out that these two issues are coupled: all the noise that is not correctly removed from the measurements could be misinterpreted as nonlinearities, and if nonlinearities are not accurately estimated, they will end up within the noise signal and information about the system under study will be lost. The underlying idea consists here in extracting the maximum of available linear and nonlinear deterministic information from measurements without misinterpreting noise.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/107802016-01-01T00:00:00ZREBILLAT, MarcEGE, KeremMECHBAL, NazihANTONI, JérômeSystems and structures are generally assumed to behave linearly and in a noise-free environment. This is in practice not perfectly the case. First, nonlinear phenomena can appear and second, the presence of noise is unavoidable for all experimental measurements. Nonlinearities can be considered as a deterministic process in the sense that in the absence of noise the output signal depends only on the input signal. Noise is purely stochastic: in the absence of an input signal, the output signal is not null and cannot be predicted at any arbitrary instant. It turns out that these two issues are coupled: all the noise that is not correctly removed from the measurements could be misinterpreted as nonlinearities, and if nonlinearities are not accurately estimated, they will end up within the noise signal and information about the system under study will be lost. The underlying idea consists here in extracting the maximum of available linear and nonlinear deterministic information from measurements without misinterpreting noise.Signal-based versus nonlinear model-based damage sensitive features for delamination quantification in CFRP composites
http://hdl.handle.net/10985/12376
Signal-based versus nonlinear model-based damage sensitive features for delamination quantification in CFRP composites
GHRIB, Meriem; REBILLAT, Marc; MECHBAL, Nazih; BERTHE, Laurent; GUSKOV, Mikhail
Structural health monitoring (SHM) is an emerging technology designed to automate the inspection process undertaken to assess the health condition of structures. The SHM process is classically decomposed into four sequential steps: detection, localization, classification, and quantification. In this paper, SHM quantification step is addressed. Particularly, we approach delamination quantification as a classification problem whereby each class corresponds to a certain damage extent. Starting from the assumption that damage causes a structure to exhibit nonlinear response, we investigate whether the use of nonlinear model based features increases classification performance. A support Vector Machine (SVM) is used to perform multi-class classification task. Two types of features are used to feed the SVM algorithm: Signal Based Features (SBF) and Nonlinear Model Based Features (NMBF). SBF are rooted in a direct use of response signals and do not consider any underlying model of the test structure. NMBF are computed based on parallel Hammerstein models which are identified with an Exponential Sine Sweep (ESS) signal. Dimensionality reduction of features vector using Principal Component Analysis (PCA) is also carried out in order to find out if it allows robustifying the quantification process suggested in this work. Experimental results on Carbon Fiber Reinforced Polymer (CFRP) composite plates equipped with piezoelectric elements and containing various delamination severities are considered for demonstration. Delamination-type damage is introduced into samples in a calibrated way using Laser Shock Wave Technique (LSWT) and more particularly symmetrical laser shock configuration. LSWT is chosen as an alternative to conventional damage generation techniques such as conventional impacts and Teflon inserts since it allows for a better calibration of damage in type, depth and size. Results show that by introducing NMBF, classification performance is improved. Furthermore, PCA allows for higher recognition rates while reducing features vector dimension.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/123762017-01-01T00:00:00ZGHRIB, MeriemREBILLAT, MarcMECHBAL, NazihBERTHE, LaurentGUSKOV, MikhailStructural health monitoring (SHM) is an emerging technology designed to automate the inspection process undertaken to assess the health condition of structures. The SHM process is classically decomposed into four sequential steps: detection, localization, classification, and quantification. In this paper, SHM quantification step is addressed. Particularly, we approach delamination quantification as a classification problem whereby each class corresponds to a certain damage extent. Starting from the assumption that damage causes a structure to exhibit nonlinear response, we investigate whether the use of nonlinear model based features increases classification performance. A support Vector Machine (SVM) is used to perform multi-class classification task. Two types of features are used to feed the SVM algorithm: Signal Based Features (SBF) and Nonlinear Model Based Features (NMBF). SBF are rooted in a direct use of response signals and do not consider any underlying model of the test structure. NMBF are computed based on parallel Hammerstein models which are identified with an Exponential Sine Sweep (ESS) signal. Dimensionality reduction of features vector using Principal Component Analysis (PCA) is also carried out in order to find out if it allows robustifying the quantification process suggested in this work. Experimental results on Carbon Fiber Reinforced Polymer (CFRP) composite plates equipped with piezoelectric elements and containing various delamination severities are considered for demonstration. Delamination-type damage is introduced into samples in a calibrated way using Laser Shock Wave Technique (LSWT) and more particularly symmetrical laser shock configuration. LSWT is chosen as an alternative to conventional damage generation techniques such as conventional impacts and Teflon inserts since it allows for a better calibration of damage in type, depth and size. Results show that by introducing NMBF, classification performance is improved. Furthermore, PCA allows for higher recognition rates while reducing features vector dimension.Wave damping and evanescence: how to combine the spatial and temporal visions of the same problem? 1
http://hdl.handle.net/10985/10854
Wave damping and evanescence: how to combine the spatial and temporal visions of the same problem? 1
BALMES, Etienne; REBILLAT, Marc; ARLAUD, Elodie
It is proposed to analyze the forced response of periodic structures using a 2D Fourier transform using continuous time and discrete space. The simple example of compression waves is used to show that this response can be used to define poles in the wavenumber domain corresponding to evanescent waves or poles in the frequency domain corresponding to damped periodic modes. Link with classical computational methods based on FEM models of cells was done for both the periodic solution and wave based approach (SAFE, WFE). Two examples are analyzed in more detail: a simple train track model exhibiting a band-gap and the more complex case of a honeycomb panel where cell wall bending occurs within the band of interest.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/108542016-01-01T00:00:00ZBALMES, EtienneREBILLAT, MarcARLAUD, ElodieIt is proposed to analyze the forced response of periodic structures using a 2D Fourier transform using continuous time and discrete space. The simple example of compression waves is used to show that this response can be used to define poles in the wavenumber domain corresponding to evanescent waves or poles in the frequency domain corresponding to damped periodic modes. Link with classical computational methods based on FEM models of cells was done for both the periodic solution and wave based approach (SAFE, WFE). Two examples are analyzed in more detail: a simple train track model exhibiting a band-gap and the more complex case of a honeycomb panel where cell wall bending occurs within the band of interest.Optimal dual-PZT sizing and network design for baseline-free SHM of complex anisotropic composite structures
http://hdl.handle.net/10985/13695
Optimal dual-PZT sizing and network design for baseline-free SHM of complex anisotropic composite structures
MECHBAL, Nazih; BOLZMACHER, Christian; LIZE, Emmanuel; REBILLAT, Marc
Structural Health Monitoring (SHM) processes for aeronautic composite structures are generally based on the comparison between healthy and unknown databases. The need for prior baseline signals is one of the barriers to an industrial deployment and can be avoided with “baseline-free” SHM (BF-SHM) methods based on the attenuations and reflections of symmetric and antisymmetric Lamb waves modes attributable to a damage. A promising mode decomposition method is based on the use of dual PZTs (concentric disc and ring electrodes lying on a single PZT). However, performances of such methods highly depend on the Lamb wave modes properties (propagation speed and attenuation that vary with material orientation and inter-PZT distance), the number and the sensitivity of the dual PZT to each mode (which depends on the frequency and element size). Considering these constraints, an original three-step process able to design a full dual-PZT network and the optimal range of excitation frequencies to consider on a highly anisotropic and arbitrarily complex aeronautic structure is presented. First, the dispersion curves of Lamb waves in the investigated material together with the minimal size of the damage to detect are used to estimate the size of the dual PZT as well as convenient excitation frequencies. A Local Finite Element Model representative of the full-scale structure is then used to estimate optimal distance and orientation between neighbor PZTs elements. Finally, a network optimization solver applies these parameters to place dual-PZTs on a fan cowl of an aircraft nacelle and provides a candidate network covering the whole structure.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/136952018-01-01T00:00:00ZMECHBAL, NazihBOLZMACHER, ChristianLIZE, EmmanuelREBILLAT, MarcStructural Health Monitoring (SHM) processes for aeronautic composite structures are generally based on the comparison between healthy and unknown databases. The need for prior baseline signals is one of the barriers to an industrial deployment and can be avoided with “baseline-free” SHM (BF-SHM) methods based on the attenuations and reflections of symmetric and antisymmetric Lamb waves modes attributable to a damage. A promising mode decomposition method is based on the use of dual PZTs (concentric disc and ring electrodes lying on a single PZT). However, performances of such methods highly depend on the Lamb wave modes properties (propagation speed and attenuation that vary with material orientation and inter-PZT distance), the number and the sensitivity of the dual PZT to each mode (which depends on the frequency and element size). Considering these constraints, an original three-step process able to design a full dual-PZT network and the optimal range of excitation frequencies to consider on a highly anisotropic and arbitrarily complex aeronautic structure is presented. First, the dispersion curves of Lamb waves in the investigated material together with the minimal size of the damage to detect are used to estimate the size of the dual PZT as well as convenient excitation frequencies. A Local Finite Element Model representative of the full-scale structure is then used to estimate optimal distance and orientation between neighbor PZTs elements. Finally, a network optimization solver applies these parameters to place dual-PZTs on a fan cowl of an aircraft nacelle and provides a candidate network covering the whole structure.Dual PZT sizing for mode decomposition on a composite anisotropic plate
http://hdl.handle.net/10985/13776
Dual PZT sizing for mode decomposition on a composite anisotropic plate
LIZE, Emmanuel; REBILLAT, Marc; MECHBAL, Nazih; BOLZMACHER, Christian
Structural Health Monitoring is a multidisciplinary field whose aim is to monitor damages within structures. Damages are detected by means of features - Damage Index (DI) - obtained by comparing measurements obtained from an unknown state with data obtained from a reference state stored in a baseline. Most DIs are calculated using Lamb wave signals generated and received by surface-mounted piezoceramic transducers (PZT) excited around a predefined central frequency. Usually, only the faster mode (S0) is considered on composite structures. However, the symmetric and antisymmetric Lamb wave modes tend to highlight different kinds of damages and are both interesting for SHM purpose. For example, a delamination in a composite plate attenuates the antisymmetric mode and reflects the symmetric one. Using two concentric PZTs (a disc and a ring defining a dual PZT) allows the decomposition of both mode contributions in the received signal. The current work presents a method based on Lamb Wave dispersion curves able to size the dual PZT and to determine the excitation frequencies to use for SHM application. This approach is based on three main observations: (i) Only the first symmetric and antisymmetric modes S0 and A0 must be generated, (ii) the dual PZT used as actuator and the excitation frequencies of the signal used must guarantee the actuation of S0 and/or A0 modes with wave length small enough to interact with the targeted minimal damage size, and (iii) the dual PZT used as sensor must be sensitive to both S0 and A0 modes on the selected range of excitation frequency. This method is applied for the sizing of dual PZT bounded to a highly anisotropic composite plate (CFRP [0,90]16) with a thickness of 2 mm and a minimal targeted damage size of 20 mm. Optimal dimensions of the PZT disk and ring are found and results of mode decomposition method on the optimal range of excitation frequencies obtained on a finite element model are presented. This simple method provides an efficient way for dual-PZT sizing in a SHM context where both S0 and A0 modes are investigated.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/137762018-01-01T00:00:00ZLIZE, EmmanuelREBILLAT, MarcMECHBAL, NazihBOLZMACHER, ChristianStructural Health Monitoring is a multidisciplinary field whose aim is to monitor damages within structures. Damages are detected by means of features - Damage Index (DI) - obtained by comparing measurements obtained from an unknown state with data obtained from a reference state stored in a baseline. Most DIs are calculated using Lamb wave signals generated and received by surface-mounted piezoceramic transducers (PZT) excited around a predefined central frequency. Usually, only the faster mode (S0) is considered on composite structures. However, the symmetric and antisymmetric Lamb wave modes tend to highlight different kinds of damages and are both interesting for SHM purpose. For example, a delamination in a composite plate attenuates the antisymmetric mode and reflects the symmetric one. Using two concentric PZTs (a disc and a ring defining a dual PZT) allows the decomposition of both mode contributions in the received signal. The current work presents a method based on Lamb Wave dispersion curves able to size the dual PZT and to determine the excitation frequencies to use for SHM application. This approach is based on three main observations: (i) Only the first symmetric and antisymmetric modes S0 and A0 must be generated, (ii) the dual PZT used as actuator and the excitation frequencies of the signal used must guarantee the actuation of S0 and/or A0 modes with wave length small enough to interact with the targeted minimal damage size, and (iii) the dual PZT used as sensor must be sensitive to both S0 and A0 modes on the selected range of excitation frequency. This method is applied for the sizing of dual PZT bounded to a highly anisotropic composite plate (CFRP [0,90]16) with a thickness of 2 mm and a minimal targeted damage size of 20 mm. Optimal dimensions of the PZT disk and ring are found and results of mode decomposition method on the optimal range of excitation frequencies obtained on a finite element model are presented. This simple method provides an efficient way for dual-PZT sizing in a SHM context where both S0 and A0 modes are investigated.