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http://hdl.handle.net/10985/8234
Optimal Sensors Placement to Enhance Damage Detection in Composite Plates
FENDZI, Claude; MOREL, Julien; REBILLAT, Marc; GUSKOV, Mikhail; MECHBAL, Nazih; COFFIGNAL, Gérard
This paper examines an important challenge in ultrasonic structural health monitoring (SHM), which is the problem of the optimal placement of sensors in order to accurately detect and localize damages. The goal of this study is to enhance damage detection through an optimal sensor placement (OSP) algorithm. The problem is formulated as a global optimization problem, where the objective function to be maximized is evaluated by a ray tracing approach, which approximately models Lamb waves propagation. A genetic algorithm (GA) is then used to solve this optimization problem. Simulations and experiments were conducted to validate the proposed method on a carbon epoxy composite plate. Results show the effectiveness and the advantages of the proposed method as a tool for OSP with reasonable computation time.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10985/82342014-01-01T00:00:00ZFENDZI, ClaudeMOREL, JulienREBILLAT, MarcGUSKOV, MikhailMECHBAL, NazihCOFFIGNAL, GérardThis paper examines an important challenge in ultrasonic structural health monitoring (SHM), which is the problem of the optimal placement of sensors in order to accurately detect and localize damages. The goal of this study is to enhance damage detection through an optimal sensor placement (OSP) algorithm. The problem is formulated as a global optimization problem, where the objective function to be maximized is evaluated by a ray tracing approach, which approximately models Lamb waves propagation. A genetic algorithm (GA) is then used to solve this optimization problem. Simulations and experiments were conducted to validate the proposed method on a carbon epoxy composite plate. Results show the effectiveness and the advantages of the proposed method as a tool for OSP with reasonable computation time.Effects of temperature on the impedance of piezoelectric actuators used for SHM
http://hdl.handle.net/10985/8222
Effects of temperature on the impedance of piezoelectric actuators used for SHM
BALMES, Etienne; GUSKOV, Mikhail; REBILLAT, Marc; MECHBAL, Nazih
— FEM modeling of piezoelectric patches used as actuators and sensors for SHM applications. — Test/analysis correlation of temperature effects in piezoelectric materials and glue — Numerical methods associated with the prediction of electric transfers.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10985/82222014-01-01T00:00:00ZBALMES, EtienneGUSKOV, MikhailREBILLAT, MarcMECHBAL, Nazih— FEM modeling of piezoelectric patches used as actuators and sensors for SHM applications. — Test/analysis correlation of temperature effects in piezoelectric materials and glue — Numerical methods associated with the prediction of electric transfers.Repeated exponential sine sweeps for the autonomous estimation of nonlinearities and bootstrap assessment of uncertainties
http://hdl.handle.net/10985/10522
Repeated exponential sine sweeps for the autonomous estimation of nonlinearities and bootstrap assessment of uncertainties
REBILLAT, Marc; EGE, Kerem; GALLO, Maxime; ANTONI, Jérôme
Measurements on vibrating structures has been a topic of interest for decades. Vibrating structures are however generally assumed to behave linearly and in a noise-free environment, which is not the case in practice. This paper provides a methodology that allows for the autonomous estimation of nonlinearities and assessment of uncertainties 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 uncertainties are simultaneously assessed using repetitions of the input signal (multi-sine sweeps) as the input of a bootstrap procedure. Mathematical foundations and a practical implementation of the method are discussed using 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 evolution of nonlinearities and uncertainties over a wide range of frequencies and input amplitudes.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/105222015-01-01T00:00:00ZREBILLAT, MarcEGE, KeremGALLO, MaximeANTONI, JérômeMeasurements on vibrating structures has been a topic of interest for decades. Vibrating structures are however generally assumed to behave linearly and in a noise-free environment, which is not the case in practice. This paper provides a methodology that allows for the autonomous estimation of nonlinearities and assessment of uncertainties 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 uncertainties are simultaneously assessed using repetitions of the input signal (multi-sine sweeps) as the input of a bootstrap procedure. Mathematical foundations and a practical implementation of the method are discussed using 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 evolution of nonlinearities and uncertainties over a wide range of frequencies and input amplitudes.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.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.Detection of structural damage using the exponential sine sweep method
http://hdl.handle.net/10985/7399
Detection of structural damage using the exponential sine sweep method
REBILLAT, Marc; HAJRYA, Rafik; MECHBAL, Nazih
Structural damages can result in nonlinear dynamical responses. Thus, estimating the nonlinearities generated by damages potentially allows detecting them. In this paper, an original approach called the ES2D (Exponential Sine Sweep Damage Detection) is proposed for nonlinear damage detection. This approach is based on a damage index that reflects the ratio of the energy contained in the nonlinear part of the output versus the energy contained in its linear part. For this, we suppose that the system under study can be modeled as a cascade of Hammerstein models, made of N branches in parallel composed of an elevation to the nth power followed by a linear filter called the nth order kernel. The Exponential Sine Sweep Method (ESSM) is then used to identify the linear and nonlinear parts of the model. Exponential sine sweeps are a class of sine sweeps that allow estimating a system’s first kernels in a wide frequency band from only one measurement. The ES2D method is illustrated experimentally on two actual composite plates with surface-mounted PZT-elements: one healthy and one damaged (impact). A given propagation path between a sensor and an actuator in the system is here under investigation. Using the ESSM, the first kernels modeling this propagation path are estimated for both the damaged and undamaged states. On the basis of these estimated first Kernels, the damage index is built. Its detecting efficiency and its insensitivity to environmental noise are then assessed.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/73992013-01-01T00:00:00ZREBILLAT, MarcHAJRYA, RafikMECHBAL, NazihStructural damages can result in nonlinear dynamical responses. Thus, estimating the nonlinearities generated by damages potentially allows detecting them. In this paper, an original approach called the ES2D (Exponential Sine Sweep Damage Detection) is proposed for nonlinear damage detection. This approach is based on a damage index that reflects the ratio of the energy contained in the nonlinear part of the output versus the energy contained in its linear part. For this, we suppose that the system under study can be modeled as a cascade of Hammerstein models, made of N branches in parallel composed of an elevation to the nth power followed by a linear filter called the nth order kernel. The Exponential Sine Sweep Method (ESSM) is then used to identify the linear and nonlinear parts of the model. Exponential sine sweeps are a class of sine sweeps that allow estimating a system’s first kernels in a wide frequency band from only one measurement. The ES2D method is illustrated experimentally on two actual composite plates with surface-mounted PZT-elements: one healthy and one damaged (impact). A given propagation path between a sensor and an actuator in the system is here under investigation. Using the ESSM, the first kernels modeling this propagation path are estimated for both the damaged and undamaged states. On the basis of these estimated first Kernels, the damage index is built. Its detecting efficiency and its insensitivity to environmental noise are then assessed.Peaks Over Threshold–based detector design for structural health monitoring: Application to aerospace structures
http://hdl.handle.net/10985/11775
Peaks Over Threshold–based detector design for structural health monitoring: Application to aerospace structures
REBILLAT, Marc; HMAD, ouadie; KADRI, farid; MECHBAL, Nazih
Structural health monitoring offers new approaches to interrogate the integrity of complex structures. The structural health monitoring process classically relies on four sequential steps: damage detection, localization, classification, and quantification. The most critical step of such process is the damage detection step since it is the first one and because performances of the following steps depend on it. A common method to design such a detector consists of relying on a statistical characterization of the damage indexes available in the healthy behavior of the structure. On the basis of this information, a decision threshold can then be computed in order to achieve a desired probability of false alarm. To determine the decision threshold corresponding to such desired probability of false alarm, the approach considered here is based on a model of the tail of the damage indexes distribution built using the Peaks Over Threshold method extracted from the extreme value theory. This approach of tail distribution estimation is interesting since it is not necessary to know the whole distribution of the damage indexes to develop a detector, but only its tail. This methodology is applied here in the context of a composite aircraft nacelle (where desired probability of false alarm is typically between 1024 and 1029) for different configurations of learning sample size and probability of false alarm and is compared to a more classical one which consists of modeling the entire damage indexes distribution by means of Parzen windows. Results show that given a set of data in the healthy state, the effective probability of false alarm obtained using the Peaks Over Threshold method is closer to the desired probability of false alarm than the one obtained using the Parzen-window method, which appears to be more conservative.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/117752018-01-01T00:00:00ZREBILLAT, MarcHMAD, ouadieKADRI, faridMECHBAL, NazihStructural health monitoring offers new approaches to interrogate the integrity of complex structures. The structural health monitoring process classically relies on four sequential steps: damage detection, localization, classification, and quantification. The most critical step of such process is the damage detection step since it is the first one and because performances of the following steps depend on it. A common method to design such a detector consists of relying on a statistical characterization of the damage indexes available in the healthy behavior of the structure. On the basis of this information, a decision threshold can then be computed in order to achieve a desired probability of false alarm. To determine the decision threshold corresponding to such desired probability of false alarm, the approach considered here is based on a model of the tail of the damage indexes distribution built using the Peaks Over Threshold method extracted from the extreme value theory. This approach of tail distribution estimation is interesting since it is not necessary to know the whole distribution of the damage indexes to develop a detector, but only its tail. This methodology is applied here in the context of a composite aircraft nacelle (where desired probability of false alarm is typically between 1024 and 1029) for different configurations of learning sample size and probability of false alarm and is compared to a more classical one which consists of modeling the entire damage indexes distribution by means of Parzen windows. Results show that given a set of data in the healthy state, the effective probability of false alarm obtained using the Peaks Over Threshold method is closer to the desired probability of false alarm than the one obtained using the Parzen-window method, which appears to be more conservative.Automatic Damage Quantification Using Signal Based And Nonlinear Model Based Damage Sensitive Features
http://hdl.handle.net/10985/12043
Automatic Damage Quantification Using Signal Based And Nonlinear Model Based Damage Sensitive Features
GHRIB, Meriem; REBILLAT, Marc; MECHBAL, Nazih; VERMOT, Guillaume
Structural Health Monitoring (SHM) can be de ned as the process of acquiring and analyzing data from on-board sensors to evaluate the health of a structure. Classically, an SHM process can be performed in four steps: detection, localization, classi cation and quanti cation. This paper addresses damage quanti cation issue as a classi cation 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 classi cation performance. A support Vector Machine (SVM) is used to perform multi-class classi cation task. Two types of features are used as inputs to 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 identi ed with an Exponential Sine Sweep (ESS) signal. A study of the sensitivity of classi cation performance to the noise contained in output signals is also conducted. Dimension reduction of features vector using Principal Component Analysis (PCA) is carried out in order to nd out if it allows robustifying the quanti cation process suggested in this work. Simulation results on a cantilever beam with a bilinear torsion spring sti ness are considered for demonstration. Results show that by introducing NMBF, classi cation performance is improved. Furthermore, PCA allows for higher recognition rates while reducing features vector dimension. However, classi ers trained on NMBF or on principal components appear to be more sensitive to output noise than those trained on SBF.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/120432017-01-01T00:00:00ZGHRIB, MeriemREBILLAT, MarcMECHBAL, NazihVERMOT, GuillaumeStructural Health Monitoring (SHM) can be de ned as the process of acquiring and analyzing data from on-board sensors to evaluate the health of a structure. Classically, an SHM process can be performed in four steps: detection, localization, classi cation and quanti cation. This paper addresses damage quanti cation issue as a classi cation 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 classi cation performance. A support Vector Machine (SVM) is used to perform multi-class classi cation task. Two types of features are used as inputs to 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 identi ed with an Exponential Sine Sweep (ESS) signal. A study of the sensitivity of classi cation performance to the noise contained in output signals is also conducted. Dimension reduction of features vector using Principal Component Analysis (PCA) is carried out in order to nd out if it allows robustifying the quanti cation process suggested in this work. Simulation results on a cantilever beam with a bilinear torsion spring sti ness are considered for demonstration. Results show that by introducing NMBF, classi cation performance is improved. Furthermore, PCA allows for higher recognition rates while reducing features vector dimension. However, classi ers trained on NMBF or on principal components appear to be more sensitive to output noise than those trained on SBF.Damage type classification based on structures nonlinear dynamical signature
http://hdl.handle.net/10985/10036
Damage type classification based on structures nonlinear dynamical signature
BAKIR, Myriam; REBILLAT, Marc; MECHBAL, Nazih
Structural damages result in nonlinear dynamical signatures that significantly help for their monitoring. A damage type classification approach is proposed here that is based on a parallel Hammerstein models representation of the structure estimated by means of the Exponential Sine Sweep Method. This estimation method has been here extended to take into account for input signal amplitude which was not the case before. On the basis of these estimated models, three amplitude dependent damage indexes are built: one that monitors the shift of the resonance frequency of the structure, another the ratio of nonlinear versus linear energy in the output signal, and a last one the ratio of the energy coming from odd nonlinearities to the energy coming from even nonlinearities in the output signal. The slopes of these amplitude-dependent DIs are then used as coordinates to place the damaged structure under study within a three-dimensional space. A single mass-spring-damper system is considered to illustrate the ability of this space to classify different types of damage. Four types of damage with different severities are simulated through different spring nonlinearities: bilinear stiffness, dead zone, saturation, and Coulomb friction. For all severities, the four types of damage are extremely well separated within the proposed three-dimensional space, thus highlighting its high potential for classification purposes.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/100362015-01-01T00:00:00ZBAKIR, MyriamREBILLAT, MarcMECHBAL, NazihStructural damages result in nonlinear dynamical signatures that significantly help for their monitoring. A damage type classification approach is proposed here that is based on a parallel Hammerstein models representation of the structure estimated by means of the Exponential Sine Sweep Method. This estimation method has been here extended to take into account for input signal amplitude which was not the case before. On the basis of these estimated models, three amplitude dependent damage indexes are built: one that monitors the shift of the resonance frequency of the structure, another the ratio of nonlinear versus linear energy in the output signal, and a last one the ratio of the energy coming from odd nonlinearities to the energy coming from even nonlinearities in the output signal. The slopes of these amplitude-dependent DIs are then used as coordinates to place the damaged structure under study within a three-dimensional space. A single mass-spring-damper system is considered to illustrate the ability of this space to classify different types of damage. Four types of damage with different severities are simulated through different spring nonlinearities: bilinear stiffness, dead zone, saturation, and Coulomb friction. For all severities, the four types of damage are extremely well separated within the proposed three-dimensional space, thus highlighting its high potential for classification purposes.Contrôle santé des structures basé sur la signature dynamique non-linéaire de dommages
http://hdl.handle.net/10985/10368
Contrôle santé des structures basé sur la signature dynamique non-linéaire de dommages
REBILLAT, Marc
La mise en place de procédures de contrôle automatisé de l’endommagement de structures issues de l’aéronautique ou du génie civil constitue une thématique émergente nommée « Contrôle de la santé des structures » (SHM : « Structural Health Monitoring »). Le déploiement de ces procédures laisse présager d’importantes améliorations en termes de sécurité ainsi qu’une réduction substantielle des couts de maintenance. Les procédures de SHM sont habituellement divisées séquentiellement en quatre étapes : détection, localisation, classification, puis quantification de l’endommagement. Les dommages apparaissant dans ces structures sont à l’origine de non-linéarités dans la réponse dynamique de ces structures qui ne sont pour l’instant pas ou peu utilisées à des fins de SHM. Nous verrons ainsi dans ce séminaire que, s’il est possible d’estimer efficacement la signature non-linéaire des dommages, cette information s’avère être un indicateur extrêmement sensible pour la surveillance des dommages. Du point de vue mathématique les travaux présentés ici s’appuient sur une classe de modèles non-linéaires par bloc prometteuse : les modèles de Hammerstein en parallèle. L’intérêt de cette classe de modèles est qu’elle est à la fois simple à estimer et représentative d’un large panel de structures endommagées. Nous verrons ainsi, qu’à partir d’une représentation non-linéaire plus riche tirée de ces modèles, des algorithmes de SHMs liés aux phases de détection, de classification, et de quantification des dommages peuvent être développés. Ces algorithmes seront illustrés dans des contextes « aéronautique » ou « génie civil » sur des données numériques et expérimentales.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/103682015-01-01T00:00:00ZREBILLAT, MarcLa mise en place de procédures de contrôle automatisé de l’endommagement de structures issues de l’aéronautique ou du génie civil constitue une thématique émergente nommée « Contrôle de la santé des structures » (SHM : « Structural Health Monitoring »). Le déploiement de ces procédures laisse présager d’importantes améliorations en termes de sécurité ainsi qu’une réduction substantielle des couts de maintenance. Les procédures de SHM sont habituellement divisées séquentiellement en quatre étapes : détection, localisation, classification, puis quantification de l’endommagement. Les dommages apparaissant dans ces structures sont à l’origine de non-linéarités dans la réponse dynamique de ces structures qui ne sont pour l’instant pas ou peu utilisées à des fins de SHM. Nous verrons ainsi dans ce séminaire que, s’il est possible d’estimer efficacement la signature non-linéaire des dommages, cette information s’avère être un indicateur extrêmement sensible pour la surveillance des dommages. Du point de vue mathématique les travaux présentés ici s’appuient sur une classe de modèles non-linéaires par bloc prometteuse : les modèles de Hammerstein en parallèle. L’intérêt de cette classe de modèles est qu’elle est à la fois simple à estimer et représentative d’un large panel de structures endommagées. Nous verrons ainsi, qu’à partir d’une représentation non-linéaire plus riche tirée de ces modèles, des algorithmes de SHMs liés aux phases de détection, de classification, et de quantification des dommages peuvent être développés. Ces algorithmes seront illustrés dans des contextes « aéronautique » ou « génie civil » sur des données numériques et expérimentales.