Model-based damage reconstruction in composites from ultrasound transmission

Fahim, A.A.; Gallego, Rafael; Bochud, Nicolás; Rus, Guillermo

doi:10.1016/j.compositesb.2012.09.003

Cited by 21 publications

(10 citation statements)

References 34 publications

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“…Damages were generated by applying several free-fall impact energies (0.388, 0.674, 1.313, 2.280, and 5.385 Joules) [11], varying the mass and height of each impactor to obtain five relevant damage locations. The specimen was excited by a low-frequency ultrasonic sine-burst at a central frequency of 5 MHz, consisting of one cycle of 0.2 µs and 5 Vpp amplitude.…”

Section: Methodsmentioning

confidence: 99%

“…Results showed that cepstra extracted from these models, in which coefficients were distributed at several lags, were more discriminative than other spectral estimation methods. In the present work, we propose an analysisby-synthesis scheme, which compares the predicted signals with the ones obtained from laboratory experiments conducted on a CFRP plate [11]. In such a way, by means of a minimization procedure, we obtain the optimal order and extent of the model parameters, and thus show that a sparse signal model may be an useful tool to model wave propagation phenomena in multilayered materials.…”

Section: Introductionmentioning

confidence: 97%

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Sparse signal model for ultrasonic nondestructive evaluation of CFRP composite plates

Bochud

Gómez

Rus

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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Signal processing has been proven to be an useful tool to characterize damaged materials under ultrasonic nondestructive evaluation. In this work, we hypothesize that the transfer function of multilayered materials for a through-transmission configuration can be represented as a classical all-pole model with sparse coefficients. To test this hypothesis, we propose an analysis-by-synthesis scheme which, by assuming an underlying sparse digital signal model of the specimen, infers the order and extent of the model parameters corresponding to a certain impact damage level. Then, we exploit the sparse structure of the obtained digital filter for practical NDE applications, with emphasis on impact damage identification of carbon-fiber reinforced polymer plates.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Sparse signal model for ultrasonic nondestructive evaluation of CFRP composite plates

Bochud

Gómez

Rus

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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“…The choice of {N max g , N p }, along with the probabilities of the genetic operators {P t = 0.7, P c = 0.8, P m = 0.1, S m = 0.1}, are empirical variables set so that the convergence to a near global optimum is guaranteed, while establishing a trade-off between the IP error and the computational cost [48]. In this work, the convergence of the algorithm was trained over a group of experimental data by examining the evolution of the currently optimal solution by increasing {N max g , N p }.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Genetic algorithms-based inversion of multimode guided waves for cortical bone characterization

et al. 2016

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Recent progress in quantitative ultrasound has exploited the multimode waveguide response of long bones. Measurements of the guided modes, along with suitable waveguide modeling, have the potential to infer strength-related factors such as stiffness (mainly determined by cortical porosity) and cortical thickness. However, the development of such model-based approaches is challenging, in particular because of the multiparametric nature of the inverse problem. Current estimation methods in the bone field rely on a number of assumptions for pairing the incomplete experimental data with the theoretical guided modes (e.g. semi-automatic selection and classification of the data). The availability of an alternative inversion scheme that is user-independent is highly desirable. Thus, this paper introduces an efficient inversion method based on genetic algorithms using multimode guided waves, in which the mode-order is kept blind. Prior to its evaluation on bone, our proposal is validated using laboratory-controlled measurements on isotropic plates and bone-mimicking phantoms. The results show that the model parameters (i.e. cortical thickness and porosity) estimated from measurements on a few ex vivo human radii are in good agreement with the reference values derived from x-ray micro-computed tomography. Further, the cortical thickness estimated from in vivo measurements at the third from the distal end of the radius is in good agreement with the values delivered by site-matched high-resolution x-ray peripheral computed tomography.

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“…A suitable approach for such comparison is given by the model-based inverse problem (IP), in either its deterministic version [8,9] or alternatively in its Bayesian (probabilistic) version [10][11][12]. The deterministic approach has been previously applied in the context of ultrasound-based damage identification in composites [7,13], although it suffers from a strong practical limitation since it requires the adoption of an a priori hypothesis about the through-the-thickness distribution of the damaged layers. However, when dealing with composite materials under fatigue or impact degradation, not only one single hypothesis about damage distribution but numerous candidate hypotheses can be considered, even under nominally identical material and testing conditions [14,15].…”

Section: Introductionmentioning

confidence: 99%

“…However, given the complexity of the internal structure of composite laminates (e.g., heterogeneity, multiple damage mechanisms, etc. ), ad hoc signal processing techniques are usually required for a more in depth interpretation of the measured ultrasonic signal [6,7]. The noise arising from the imperfections of both the acquisition system and the propagation path, and the difficulties in understanding and analyzing multiple and overlapping ultrasonic echoes, suggest to directly compare the experimental signal response with theoretical signals obtained from a model of ultrasound wave propagation (UWP), with the purpose of inferring quantitative information about the effective mechanical properties of the material.…”

Section: Introductionmentioning

confidence: 99%

A multilevel Bayesian method for ultrasound-based damage identification in composite laminates

Chiachío

Bochud

Chiachío

et al. 2017

Mechanical Systems and Signal Processing

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This version is available at https://strathprints.strath.ac.uk/65462/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Abstract Estimating deterministic single-valued damage parameters when evaluating the actual health state of a material has a limited meaning if one considers not only the existence of measurement errors, but also that the model chosen to represent the damage behavior is just an idealization of reality. This paper proposes a multilevel Bayesian inverse problem framework to deal with these sources of uncertainty in the context of ultrasound-based damage identification. Although the methodology has a broad spectrum of applicability, here it is oriented to model-based damage assessment in layered composite materials using through-transmission ultrasonic measurements. The overall procedure is first validated on synthetically generated signals and then evaluated on real signals obtained from a post-impact fatigue damage experiment in a cross-ply carbon-epoxy laminate. The evidence of the hypothesized model of damage is revealed as a suitable measure of the overall ability of that candidate hypothesis to represent the actual damage state observed by the ultrasound, thus avoiding the extremes of over-fitting or under-fitting the ultrasonic signal.

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Model-based damage reconstruction in composites from ultrasound transmission

Cited by 21 publications

References 34 publications

Sparse signal model for ultrasonic nondestructive evaluation of CFRP composite plates

Sparse signal model for ultrasonic nondestructive evaluation of CFRP composite plates

Genetic algorithms-based inversion of multimode guided waves for cortical bone characterization

A multilevel Bayesian method for ultrasound-based damage identification in composite laminates

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