A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves
Ultrasonic guided waves offer a convenient and practical approach to structural health monitoring and non-destructive evaluation. A key property of guided waves is the fully defined relationship between central frequency and propagation characteristics (phase velocity, group velocity and wavenumber)...
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Published in | Sensors (Basel, Switzerland) Vol. 23; no. 1; p. 185 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
24.12.2022
MDPI |
Subjects | |
Online Access | Get full text |
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Summary: | Ultrasonic guided waves offer a convenient and practical approach to structural health monitoring and non-destructive evaluation. A key property of guided waves is the fully defined relationship between central frequency and propagation characteristics (phase velocity, group velocity and wavenumber)-which is described using dispersion curves. For many guided wave-based strategies, accurate dispersion curve information is invaluable, such as group velocity for localisation. From experimental observations of dispersion curves, a system identification procedure can be used to determine the governing material properties. As well as returning an estimated value, it is useful to determine the distribution of these properties based on measured data. A method of simulating samples from these distributions is to use the iterative Markov-Chain Monte Carlo (MCMC) procedure, which allows for freedom in the shape of the posterior. In this work, a scanning-laser Doppler vibrometer is used to record the propagation of Lamb waves in a unidirectional-glass-fibre composite plate, and dispersion curve data for various propagation angles are extracted. Using these measured dispersion curve data, the MCMC sampling procedure is performed to provide a Bayesian approach to determining the dispersion curve information for an arbitrary plate. The distribution of the material properties at each angle is discussed, including the inferred confidence in the predicted parameters. The percentage errors of the estimated values for the parameters were 10-15 points larger when using the most likely estimates, as opposed to calculating from the posterior distributions, highlighting the advantages of using a probabilistic approach. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 This paper is an extended version of our paper published in Haywood-Alexander, M.; Dervilis, N.; Worden, K.; Rogers, T.J. A Bayesian Approach to Lamb-Wave Dispersion Curve Material identification in Composite Plates in Proceedings of European Workshop on Structural Health Monitoring (EWSHM 2022), Palermo, Italy, 4–7 July 2022. |
ISSN: | 1424-8220 1424-8220 |
DOI: | 10.3390/s23010185 |