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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.Probabilistic Decision Trees using SVM for Multi-class Classification
http://hdl.handle.net/10985/7401
Probabilistic Decision Trees using SVM for Multi-class Classification
URIBE, Juan Sebastian; MECHBAL, Nazih; REBILLAT, Marc; BOUAMAMA, Karima; PENGOV, Marco
In the automotive repairing backdrop, retrieving from previously solved incident the database features that could support and speed up the diagnostic is of great usefulness. This decision helping process should give a fixed number of the more relevant diagnostic classified in a likelihood sense. It is a probabilistic multi-class classification problem. This paper describes an original classification technique, the Probabilistic Decision Tree (PDT) producing a posteriori probabilities in a multi-class context. It is based on a Binary Decision Tree (BDT) with Probabilistic Support Vector Machine classifier (PSVM). At each node of the tree, a bi-class SVM along with a sigmoid function are trained to give a probabilistic classification output. For each branch, the outputs of all the nodes composing the branch are combined to lead to a complete evaluation of the probability when reaching the final leaf (representing the class associated to the branch). To illustrate the effectiveness of PDTs, they are tested on benchmark datasets and results are compared with other existing approaches.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/74012013-01-01T00:00:00ZURIBE, Juan SebastianMECHBAL, NazihREBILLAT, MarcBOUAMAMA, KarimaPENGOV, MarcoIn the automotive repairing backdrop, retrieving from previously solved incident the database features that could support and speed up the diagnostic is of great usefulness. This decision helping process should give a fixed number of the more relevant diagnostic classified in a likelihood sense. It is a probabilistic multi-class classification problem. This paper describes an original classification technique, the Probabilistic Decision Tree (PDT) producing a posteriori probabilities in a multi-class context. It is based on a Binary Decision Tree (BDT) with Probabilistic Support Vector Machine classifier (PSVM). At each node of the tree, a bi-class SVM along with a sigmoid function are trained to give a probabilistic classification output. For each branch, the outputs of all the nodes composing the branch are combined to lead to a complete evaluation of the probability when reaching the final leaf (representing the class associated to the branch). To illustrate the effectiveness of PDTs, they are tested on benchmark datasets and results are compared with other existing approaches.Optimal Sensors Placement to Enhance Damage Detection in Composite Plates
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.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.A data-driven temperature compensation approach for Structural Health Monitoring using Lamb waves
http://hdl.handle.net/10985/11239
A data-driven temperature compensation approach for Structural Health Monitoring using Lamb waves
FENDZI, Claude; REBILLAT, Marc; MECHBAL, Nazih; GUSKOV, Mikhail; COFFIGNAL, Gérard
This paper presents a temperature compensation method for Lamb wave structural health monitoring. The proposed approach considers a representation of the piezo-sensor signal through its Hilbert transform that allows one to extract the amplitude factor and the phase shift in signals caused by temperature changes. An ordinary least square (OLS) algorithm is used to estimate these unknown parameters. After estimating these parameters at each temperature in the operating range, linear functional relationships between the temperature and the estimated parameters are derived using the least squares method. A temperature compensation model is developed based on this linear relationship that allows one to reconstruct sensor signals at any arbitrary temperature. The proposed approach is validated numerically and experimentally for an anisotropic composite plate at different temperatures ranging from Formula to Formula . A close match is found between the measured signals and the reconstructed ones. This approach is interesting as it needs only a limited set of piezo-sensor signals at different temperatures for model training and temperature compensation at any arbitrary temperature. Damage localization results after temperature compensation demonstrate its robustness and effectiveness.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/112392016-01-01T00:00:00ZFENDZI, ClaudeREBILLAT, MarcMECHBAL, NazihGUSKOV, MikhailCOFFIGNAL, GérardThis paper presents a temperature compensation method for Lamb wave structural health monitoring. The proposed approach considers a representation of the piezo-sensor signal through its Hilbert transform that allows one to extract the amplitude factor and the phase shift in signals caused by temperature changes. An ordinary least square (OLS) algorithm is used to estimate these unknown parameters. After estimating these parameters at each temperature in the operating range, linear functional relationships between the temperature and the estimated parameters are derived using the least squares method. A temperature compensation model is developed based on this linear relationship that allows one to reconstruct sensor signals at any arbitrary temperature. The proposed approach is validated numerically and experimentally for an anisotropic composite plate at different temperatures ranging from Formula to Formula . A close match is found between the measured signals and the reconstructed ones. This approach is interesting as it needs only a limited set of piezo-sensor signals at different temperatures for model training and temperature compensation at any arbitrary temperature. Damage localization results after temperature compensation demonstrate its robustness and effectiveness.Effects of temperature on the impedance of piezoelectric actuators used for SHM
http://hdl.handle.net/10985/8591
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/10985/85912014-01-01T00:00:00ZBALMES, 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.Generation of controlled delaminations in composites using symmetrical laser shock configuration
http://hdl.handle.net/10985/11734
Generation of controlled delaminations in composites using symmetrical laser shock configuration
GHRIB, Meriem; BERTHE, Laurent; MECHBAL, Nazih; REBILLAT, Marc; GUSKOV, Mikhail; ECAULT, Romain; BEDREDDINE, Nas
Structural Health Monitoring (SHM) is defined as the process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructures. SHM can be organized into five main steps: detection, localization, classification, quantification and prognosis. Our work considers SHM quantification level and in particular the evaluation of the severity of delamination-type damage in CFRP composite laminates. Prior to quantification algorithms implementation, it is important to properly prepare the supports on which algorithms will be tested. Teflon inserts and conventional impacts are commonly used techniques to generate or simulate delaminations. However, with such rudimentary techniques it is difficult to generate controlled delamination-type damage in a realistic way. In the present work, we investigate symmetrical laser shock approach, as a new method to calibrate delaminations in composites. By tuning the time delay between the two laser beams and laser energy, through-thickness damage position and severity can respectively be adjusted. The effect of multiple contiguous laser impacts was also investigated. Post-mortem analyses using A-scan and C-scan testing as well as penetrant testing were performed in order to characterize laser impact induced damage. Results are encouraging and demonstrate the high potential of symmetrical laser shock for damage calibration in both size and location.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/117342017-01-01T00:00:00ZGHRIB, MeriemBERTHE, LaurentMECHBAL, NazihREBILLAT, MarcGUSKOV, MikhailECAULT, RomainBEDREDDINE, NasStructural Health Monitoring (SHM) is defined as the process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructures. SHM can be organized into five main steps: detection, localization, classification, quantification and prognosis. Our work considers SHM quantification level and in particular the evaluation of the severity of delamination-type damage in CFRP composite laminates. Prior to quantification algorithms implementation, it is important to properly prepare the supports on which algorithms will be tested. Teflon inserts and conventional impacts are commonly used techniques to generate or simulate delaminations. However, with such rudimentary techniques it is difficult to generate controlled delamination-type damage in a realistic way. In the present work, we investigate symmetrical laser shock approach, as a new method to calibrate delaminations in composites. By tuning the time delay between the two laser beams and laser energy, through-thickness damage position and severity can respectively be adjusted. The effect of multiple contiguous laser impacts was also investigated. Post-mortem analyses using A-scan and C-scan testing as well as penetrant testing were performed in order to characterize laser impact induced damage. Results are encouraging and demonstrate the high potential of symmetrical laser shock for damage calibration in both size and location.A General Bayesian Framework for Ellipse-based and Hyperbola-based Damage Localisation in Anisotropic Composite Plates
http://hdl.handle.net/10985/9218
A General Bayesian Framework for Ellipse-based and Hyperbola-based Damage Localisation in Anisotropic Composite Plates
FENDZI, Claude; MECHBAL, Nazih; REBILLAT, Marc; GUSKOV, Mikhail
This paper focuses on Bayesian Lamb wave-based damage localization in structural health monitoring of anisotropic composite materials. A Bayesian framework is applied to take account for uncertainties from experimental time-of-flight measurements and angular dependent group velocity within the composite material. An original parametric analytical expression of the direction dependence of group velocity is proposed and validated numerically and experimentally for anisotropic composite and sandwich plates. This expression is incorporated into time-of-arrival (ToA: ellipse-based) and time-difference-of-arrival (TDoA: hyperbola-based) Bayesian damage localization algorithms. This way, the damage location as well as the group velocity profile are estimated jointly and a priori information taken into consideration. The proposed algorithm is general as it allows to take into account for uncertainties within a Bayesian framework, and to model effects of anisotropy on group velocity. Numerical and experimental results obtained with different damage sizes or locations and for different degrees of anisotropy validate the ability of the proposed algorithm to estimate both the damage location and the group velocity profile as well as the associated confidence intervals. Results highlight the need to consider for anisotropy in order to increase localization accuracy, and to use Bayesian analysis to quantify uncertainties in damage localization.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/92182016-01-01T00:00:00ZFENDZI, ClaudeMECHBAL, NazihREBILLAT, MarcGUSKOV, MikhailThis paper focuses on Bayesian Lamb wave-based damage localization in structural health monitoring of anisotropic composite materials. A Bayesian framework is applied to take account for uncertainties from experimental time-of-flight measurements and angular dependent group velocity within the composite material. An original parametric analytical expression of the direction dependence of group velocity is proposed and validated numerically and experimentally for anisotropic composite and sandwich plates. This expression is incorporated into time-of-arrival (ToA: ellipse-based) and time-difference-of-arrival (TDoA: hyperbola-based) Bayesian damage localization algorithms. This way, the damage location as well as the group velocity profile are estimated jointly and a priori information taken into consideration. The proposed algorithm is general as it allows to take into account for uncertainties within a Bayesian framework, and to model effects of anisotropy on group velocity. Numerical and experimental results obtained with different damage sizes or locations and for different degrees of anisotropy validate the ability of the proposed algorithm to estimate both the damage location and the group velocity profile as well as the associated confidence intervals. Results highlight the need to consider for anisotropy in order to increase localization accuracy, and to use Bayesian analysis to quantify uncertainties in damage localization.