Informative Bayesian tools for damage localisation by decomposition of Lamb wave signals

Haywood-Alexander, Marcus; Dervilis, Nikolaos; Worden, Keith; Dobie, Gordon; Rogers, Timothy J.

doi:10.1016/j.jsv.2022.117063

Cited by 11 publications

(3 citation statements)

References 26 publications

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“…The excitation signal was a 3-cycle sinusoid with 387 kHz center frequency. Array 2 received A-scan signals which where post-processed to obtain a 2DFFT map [7], presented in Figure 4. The bandwidth at -12 dB is around 150 kHz covering the frequency range 312-462 kHz.…”

Section: Intact Samplementioning

confidence: 99%

The Effect of Complex Corrosion Profiles on Remaining Wall Thickness Quantification Using Shear Horizontal Guided Waves

TZAFERIS,

TABATABAEIPOUR,

DOBIE

et al. 2023

Proceedings of the 14th International Workshop on Structural Health Monitoring

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Corrosion of plate and pipe structures is a major concern to many key industries, including power, maritime, and oil and gas. When there is a need to inspect large areas quickly or when access to the structure is limited, guided wave testing is often preferred over bulk wave measurements. In this work, shear horizontal guided waves are employed for wall thickness quantification. Specifically, the interaction of modes SH1 and SH0 with complex corrosion defects is investigated. The guided wave mode are selectively generated using a phased array-based approach. A pair of identical phased array probes are positioned before and after the simulated corrosion profile, to monitor the reflected and transmitted waves. The targeted mode is excited selectively using a 32-element 3 mm pitch array and guided wave modes are decomposed after a 2DFFT is performed. The cut-off frequency technique using mode SH1 is shown to be adequate when smooth wall thinning defects are considered. When sharp pits are present, mode SH0 proved sufficient to determine the pits depth.

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Section: Intact Samplementioning

confidence: 99%

The Effect of Complex Corrosion Profiles on Remaining Wall Thickness Quantification Using Shear Horizontal Guided Waves

TZAFERIS,

TABATABAEIPOUR,

DOBIE

et al. 2023

Proceedings of the 14th International Workshop on Structural Health Monitoring

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show abstract

“…This relationship is more completely described by defining a map between the frequency and wavenumber, which can be plotted as dispersion curves . Use of dispersion curve information is essential in guided wave-based NDE and SHM strategies [ 5 , 6 , 7 ], one example being to use known group velocities for damage localisation [ 8 , 9 ]. In practice, the governing elastodynamic equations are numerically solved to determine these curves.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves

Haywood-Alexander

Dervilis

Worden

et al. 2022

Sensors

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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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“…The dispersion relationship is more completely described by defining a map between the frequency and the wavenumber, which can be plotted as dispersion curves. Use of dispersion curve information is essential in guided wave-based SHM strategies, one example being to use known group velocities for damage localisation [4,5]. In practice, the governing elastodynamic equations are numerically solved to determine these curves.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Approach to Lamb-Wave Dispersion Curve Material Identification in Composite Plates

Haywood-Alexander

Dervilis

Worden

et al. 2022

Lecture Notes in Civil Engineering

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Guided waves are gaining increased interest in SHM, thanks to some distinct advantages. For guided-wave-based localisation strategies, information on the group velocity is required; therefore, determination of accurate dispersion curves is invaluable. However, for complex materials, the wave speed is dependent on the propagation angle. From experimental observations of dispersion curves, measured using a two-dimensional Fourier transform, a system identification procedure can be used to determine the estimated value and distribution for the governing material properties. Markov-chain Monte Carlo (MCMC) sampling can provide a way of simulating samples from these distributions, which would require solving dispersion curves many times. By using a novel Legendre polynomial expansion approach, the computational cost of dispersion curve solutions is greatly reduced, making the MCMC procedure a more practical approach In this work, a scanning laser Doppler vibrometer is used to record the propagation of Lamb waves in a carbon-fibre-composite plates, and points on the dispersion curve are extracted. These observations are then fed into the MCMC material identification procedure to provide a Bayesian approach to determining properties governing Lamb wave propagation at various angles in the plate. The distribution of parameters at each angle is discussed, including the inferred confidence in the predicted parameters.

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Informative Bayesian tools for damage localisation by decomposition of Lamb wave signals

Cited by 11 publications

References 26 publications

The Effect of Complex Corrosion Profiles on Remaining Wall Thickness Quantification Using Shear Horizontal Guided Waves

The Effect of Complex Corrosion Profiles on Remaining Wall Thickness Quantification Using Shear Horizontal Guided Waves

A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves

A Bayesian Approach to Lamb-Wave Dispersion Curve Material Identification in Composite Plates

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