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http://hdl.handle.net/10985/12378
On-board Decision Making Platform for Structural Health Monitoring
BARTHES, Clément; MECHBAL, Nazih; MOSALAM, Khalid; REBILLAT, Marc
The ability to monitor the health of complex structures such as aeronautic or civil engineering structures in real time is becoming increasingly important. This process is referred to as structural health monitoring (SHM) and relies on onboard platforms comprising sensors, computational units, communication resources, and sometimes actuators. Many of such platforms have been developed within the last years but there is still a lack of structuration and knowledge exchange regarding the software and hardware architectures of such platforms. The aim of the present paper is to introduce an open hardware and open software platform dedicated to SHM within the fields of aeronautics and civil engineering. The platform presented here will be made available in an open hardware and open source framework to allow SHM researchers to run concurrent detection, localization, classification or quantification algorithms using simple interpreted languages such as Python.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/123782017-01-01T00:00:00ZBARTHES, ClémentMECHBAL, NazihMOSALAM, KhalidREBILLAT, MarcThe ability to monitor the health of complex structures such as aeronautic or civil engineering structures in real time is becoming increasingly important. This process is referred to as structural health monitoring (SHM) and relies on onboard platforms comprising sensors, computational units, communication resources, and sometimes actuators. Many of such platforms have been developed within the last years but there is still a lack of structuration and knowledge exchange regarding the software and hardware architectures of such platforms. The aim of the present paper is to introduce an open hardware and open software platform dedicated to SHM within the fields of aeronautics and civil engineering. The platform presented here will be made available in an open hardware and open source framework to allow SHM researchers to run concurrent detection, localization, classification or quantification algorithms using simple interpreted languages such as Python.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.Comparison of least squares and exponential sine sweep methods for Parallel Hammerstein Models estimation
http://hdl.handle.net/10985/12468
Comparison of least squares and exponential sine sweep methods for Parallel Hammerstein Models estimation
REBILLAT, Marc; SCHOUKENS, Maarten
Linearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, Parallel Hammerstein Models (PHM) are interesting as they are at the same time easy to interpret as well as to estimate. One way to estimate PHM relies on the fact that the estimation problem is linear in the parameters and thus that classical least squares (LS) estimation algorithms can be used. In that area, this article introduces a regularized LS estimation algorithm inspired on some of the recently developed regularized impulse response estimation techniques. Another mean to estimate PHM consists in using parametric or non-parametric exponential sine sweeps (ESS) based methods. These methods (LS and ESS) are founded on radically different mathematical backgrounds but are expected to tackle the same issue. A methodology is proposed here to compare them with respect to (i) their accuracy, (ii) their computational cost, and (iii) their robustness to noise. Tests are performed on simulated systems for several values of methods respective parameters and of signal to noise ratio. Results show that, for a given set of data points, the ESS method is less demanding in computational resources than the LS method but that it is also less accurate. Furthermore, the LS method needs parameters to be set in advance whereas the ESS method is not subject to conditioning issues and can be fully non-parametric. In summary, for a given set of data points, ESS method can provide a first, automatic, and quick overview of a nonlinear system than can guide more computationally demanding and precise methods, such as the regularized LS one proposed here.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/124682017-01-01T00:00:00ZREBILLAT, MarcSCHOUKENS, MaartenLinearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, Parallel Hammerstein Models (PHM) are interesting as they are at the same time easy to interpret as well as to estimate. One way to estimate PHM relies on the fact that the estimation problem is linear in the parameters and thus that classical least squares (LS) estimation algorithms can be used. In that area, this article introduces a regularized LS estimation algorithm inspired on some of the recently developed regularized impulse response estimation techniques. Another mean to estimate PHM consists in using parametric or non-parametric exponential sine sweeps (ESS) based methods. These methods (LS and ESS) are founded on radically different mathematical backgrounds but are expected to tackle the same issue. A methodology is proposed here to compare them with respect to (i) their accuracy, (ii) their computational cost, and (iii) their robustness to noise. Tests are performed on simulated systems for several values of methods respective parameters and of signal to noise ratio. Results show that, for a given set of data points, the ESS method is less demanding in computational resources than the LS method but that it is also less accurate. Furthermore, the LS method needs parameters to be set in advance whereas the ESS method is not subject to conditioning issues and can be fully non-parametric. In summary, for a given set of data points, ESS method can provide a first, automatic, and quick overview of a nonlinear system than can guide more computationally demanding and precise methods, such as the regularized LS one proposed here.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.From nonlinear system identification to structural health monitoring
http://hdl.handle.net/10985/11277
From nonlinear system identification to structural health monitoring
REBILLAT, Marc
The process of implementing a damage monitoring strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM) and implies a sensor network that monitors the behavior of the structure on-line. A SHM process potentially allows for an optimal use of the monitored structure, a minimized downtime, and the avoidance of catastrophic failures. The SHM process classically relies on four sequential steps that are damage detection, localization, classification, and quantification. The key idea underlying this seminary is that structural damages may result in nonlinear dynamical signatures that are not yet used in SHM despite the fact that they can significantly enhance their monitoring. We thus propose to monitor these structural damages by identifying their nonlinear signature on the basis of a cascade of Hammerstein models representation of the structure. This model is here estimated at very low computational cost by means of the Exponential Sine Sweep Method. It will be shown that on the basis of this richer dynamical representation of the structure, SHM algorithms dedicated to damage detection, classification and quantification can be derived. This will be illustrated in the aeronautic and civil engineering contexts and using experimental as well as numerical data.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/112772016-01-01T00:00:00ZREBILLAT, MarcThe process of implementing a damage monitoring strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM) and implies a sensor network that monitors the behavior of the structure on-line. A SHM process potentially allows for an optimal use of the monitored structure, a minimized downtime, and the avoidance of catastrophic failures. The SHM process classically relies on four sequential steps that are damage detection, localization, classification, and quantification. The key idea underlying this seminary is that structural damages may result in nonlinear dynamical signatures that are not yet used in SHM despite the fact that they can significantly enhance their monitoring. We thus propose to monitor these structural damages by identifying their nonlinear signature on the basis of a cascade of Hammerstein models representation of the structure. This model is here estimated at very low computational cost by means of the Exponential Sine Sweep Method. It will be shown that on the basis of this richer dynamical representation of the structure, SHM algorithms dedicated to damage detection, classification and quantification can be derived. This will be illustrated in the aeronautic and civil engineering contexts and using experimental as well as numerical data.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.Peaks Over Threshold Method for Structural Health Monitoring Detector Design
http://hdl.handle.net/10985/10377
Peaks Over Threshold Method for Structural Health Monitoring Detector Design
HMAD, Ouadie; MECHBAL, Nazih; REBILLAT, Marc
Structural Health Monitoring (SHM) system offers new approaches to interrogate the integrity of structures. The most critical step of such systems is the damage detection step since it is the first and because performances of the following steps (damage localization, severity estimation…) depend on it. Care has thus to be taken when designing the detector. The objective of this communication is to discuss issues related to the design of a detector for the structural health monitoring of composite structures. The structure under monitoring is a substructure of an aircraft nacelle. In the absence of damage, the detector principle is to statistically characterize the healthy behavior of the structure. This characterization is based on the availability of a decision statistics synthesized from a damage index. Airline business models rely on Probability of False Alarms (Pfa) as main performance criterion. In general, the requirement on Pfa is 10E-9 which is very small. To determine the decision threshold, the approach we consider, consists to model the tail of the decision statistics using the Peaks Over Threshold method extracted from the extreme value theory (EVT). This method has been applied for different configuration of learning sample and probability of false alarm. This approach of tail distribution estimation is interesting since it is not necessary to know the distribution of the decision statistic to develop a detector. However, its main drawback is that it is necessary to have very large databases to accurately estimate decision thresholds to then decide the presence or absence of damage.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/103772015-01-01T00:00:00ZHMAD, OuadieMECHBAL, NazihREBILLAT, MarcStructural Health Monitoring (SHM) system offers new approaches to interrogate the integrity of structures. The most critical step of such systems is the damage detection step since it is the first and because performances of the following steps (damage localization, severity estimation…) depend on it. Care has thus to be taken when designing the detector. The objective of this communication is to discuss issues related to the design of a detector for the structural health monitoring of composite structures. The structure under monitoring is a substructure of an aircraft nacelle. In the absence of damage, the detector principle is to statistically characterize the healthy behavior of the structure. This characterization is based on the availability of a decision statistics synthesized from a damage index. Airline business models rely on Probability of False Alarms (Pfa) as main performance criterion. In general, the requirement on Pfa is 10E-9 which is very small. To determine the decision threshold, the approach we consider, consists to model the tail of the decision statistics using the Peaks Over Threshold method extracted from the extreme value theory (EVT). This method has been applied for different configuration of learning sample and probability of false alarm. This approach of tail distribution estimation is interesting since it is not necessary to know the distribution of the decision statistic to develop a detector. However, its main drawback is that it is necessary to have very large databases to accurately estimate decision thresholds to then decide the presence or absence of damage.A multi-sine sweep method for the characterization of weak non-linearities ; plant noise and variability estimation.
http://hdl.handle.net/10985/10288
A multi-sine sweep method for the characterization of weak non-linearities ; plant noise and variability estimation.
GALLO, Maxime; EGE, Kerem; REBILLAT, Marc; ANTONI, Jérôme
Weak non-linearities in vibrating structures can be characterized by a signal-model approach based on cascade of Hammerstein models. The experiment consists in exciting a device with a sine sweep at different levels, in order to assess the evolutions of non linearities on a wide frequency range. A method developed previously, based on exponential sine sweep, is able to give an approximative identification of the Hammerstein models, but cannot make the distinction between nonlinear distortion and stationary plant noise. Therefore, this paper proposes improvements on the method that provide a more precise estimation of the Hammerstein models through the cancellation of the plant noise: it relies on the repetition of the signal on a certain amount of periods (multi-sine sweeps) and then on the consideration of the synchronous average out of the different periods from the resulting signal. Mathematical foundations and practical implementation of the method are discussed. The second main point of improvement concerning the study of the vibrating device is the use of the Bootstrap analysis. By considering some periods randomly chosen among the multisine sweep, one can study the variability of the experiments. The method becomes more robust.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/102882015-01-01T00:00:00ZGALLO, MaximeEGE, KeremREBILLAT, MarcANTONI, JérômeWeak non-linearities in vibrating structures can be characterized by a signal-model approach based on cascade of Hammerstein models. The experiment consists in exciting a device with a sine sweep at different levels, in order to assess the evolutions of non linearities on a wide frequency range. A method developed previously, based on exponential sine sweep, is able to give an approximative identification of the Hammerstein models, but cannot make the distinction between nonlinear distortion and stationary plant noise. Therefore, this paper proposes improvements on the method that provide a more precise estimation of the Hammerstein models through the cancellation of the plant noise: it relies on the repetition of the signal on a certain amount of periods (multi-sine sweeps) and then on the consideration of the synchronous average out of the different periods from the resulting signal. Mathematical foundations and practical implementation of the method are discussed. The second main point of improvement concerning the study of the vibrating device is the use of the Bootstrap analysis. By considering some periods randomly chosen among the multisine sweep, one can study the variability of the experiments. The method becomes more robust.Estimation of the temperature field on a composite fan cowl using the static capacity of surface-mounted piezoceramic transducers
http://hdl.handle.net/10985/12044
Estimation of the temperature field on a composite fan cowl using the static capacity of surface-mounted piezoceramic transducers
LIZE, Emmanuel; REBILLAT, Marc; MECHBAL, Nazih
The influence of temperature on SHM (Structural Health Monitoring) systems using guided waves is a major problem for their industrial deployment. One of the most used and cheapest SHM process developed in aeronautic context is based on piezoelectric transducers mounted on the monitored structure. Several methods are then used to assess the presence of damage. A popular one is based on tracking changes in the static capacity of the transducers: it is an efficient damage indicator in close area surrounding the device and is often used as a fault diagnosis of the transducer itself. However, monitoring decision are robustified with temperature sensors also mounted on the structure, adding wires and signal processing post-treatments. In this article, the static capacity is used to determine the temperature on each lead zirconate titanate transducer (PZT). By imparting this additional functionality to PZT devices, supplementary instrumentation is not necessary and an estimation of the entire temperature field of the structure is obtained. The original proposed approach is tested experimentally on a on a small composite plate and then on a large real part of an A380 composite nacelle. The results show that the temperature field on the structure can be estimated with a precision of ±5 °C using a linear regression between static capacity and temperature
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/120442017-01-01T00:00:00ZLIZE, EmmanuelREBILLAT, MarcMECHBAL, NazihThe influence of temperature on SHM (Structural Health Monitoring) systems using guided waves is a major problem for their industrial deployment. One of the most used and cheapest SHM process developed in aeronautic context is based on piezoelectric transducers mounted on the monitored structure. Several methods are then used to assess the presence of damage. A popular one is based on tracking changes in the static capacity of the transducers: it is an efficient damage indicator in close area surrounding the device and is often used as a fault diagnosis of the transducer itself. However, monitoring decision are robustified with temperature sensors also mounted on the structure, adding wires and signal processing post-treatments. In this article, the static capacity is used to determine the temperature on each lead zirconate titanate transducer (PZT). By imparting this additional functionality to PZT devices, supplementary instrumentation is not necessary and an estimation of the entire temperature field of the structure is obtained. The original proposed approach is tested experimentally on a on a small composite plate and then on a large real part of an A380 composite nacelle. The results show that the temperature field on the structure can be estimated with a precision of ±5 °C using a linear regression between static capacity and temperatureParallel Hammerstein Models Identification using Sine Sweeps and the Welch Method
http://hdl.handle.net/10985/12377
Parallel Hammerstein Models Identification using Sine Sweeps and the Welch Method
BOUTILLON, Xavier; CORTEEL, Etienne; REBILLAT, Marc; ROGGERONE, Vincent
Linearity is a common assumption for many real life systems. But in many cases, the nonlinear behavior of systems cannot be ignored and has to be modeled and estimated. Among the various classes of nonlinear models present in the literature, Parallel Hammertein Models (PHM) are interesting as they are at the same time easy to understand as well as to estimate when using exponential sine sweeps (ESS) based methods. However, the classical EES- based estimation procedure for PHM relies on a very speci c input signal (ESS), which limits its use in practice. A method is proposed here based on the Welch method that allows for PHM estimation with arbitrary sine sweeps (ASS) which are a much broader class of input signals than ESS. Results show that for various ASS, the proposed method provides results that are in excellent agreement with the ones obtained with the classical ESS method.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/123772017-01-01T00:00:00ZBOUTILLON, XavierCORTEEL, EtienneREBILLAT, MarcROGGERONE, VincentLinearity is a common assumption for many real life systems. But in many cases, the nonlinear behavior of systems cannot be ignored and has to be modeled and estimated. Among the various classes of nonlinear models present in the literature, Parallel Hammertein Models (PHM) are interesting as they are at the same time easy to understand as well as to estimate when using exponential sine sweeps (ESS) based methods. However, the classical EES- based estimation procedure for PHM relies on a very speci c input signal (ESS), which limits its use in practice. A method is proposed here based on the Welch method that allows for PHM estimation with arbitrary sine sweeps (ASS) which are a much broader class of input signals than ESS. Results show that for various ASS, the proposed method provides results that are in excellent agreement with the ones obtained with the classical ESS method.