Multihelical Lamb Wave Imaging for Pipe-Like Structures Based on a Probabilistic Reconstruction Approach

Wang, Zhe; Huang, Songling; Wang, Shen; Wang, Qing; Zhao, Wei

doi:10.1109/tim.2020.3038474

Cited by 14 publications

(5 citation statements)

References 41 publications

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“…Ultrasonic guided waves comprise one of these techniques, and are currently revolutionizing the approach to NDT and SHM [5] because of their high sensitivity to minor damage and their online monitoring capabilities. Guided wave testing has been applied to various structural forms, including plates [6,7], beams [8,9], pipes [10,11], and adhesive joints [12], and several different damage assessment methods have been presented.…”

Section: Introductionmentioning

confidence: 99%

Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme

Cantero‐Chinchilla

Yan

et al. 2023

Sensors

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In this paper, defect detection and identification in aluminium joints is investigated based on guided wave monitoring. Guided wave testing is first performed on the selected damage feature from experiments, namely, the scattering coefficient, to prove the feasibility of damage identification. A Bayesian framework based on the selected damage feature for damage identification of three-dimensional joints of arbitrary shape and finite size is then presented. This framework accounts for both modelling and experimental uncertainties. A hybrid wave and finite element approach (WFE) is adopted to predict the scattering coefficients numerically corresponding to different size defects in joints. Moreover, the proposed approach leverages a kriging surrogate model in combination with WFE to formulate a prediction equation that links scattering coefficients to defect size. This equation replaces WFE as the forward model in probabilistic inference, resulting in a significant enhancement in computational efficiency. Finally, numerical and experimental case studies are used to validate the damage identification scheme. An investigation into how the location of sensors can impact the identified results is provided as well.

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Section: Introductionmentioning

confidence: 99%

Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme

Cantero‐Chinchilla

Yan

et al. 2023

Sensors

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“…However, the Lamb waves have some limitations related to the properties of these waves such as: a dispersion phenomenon, multimodal behavior, convergence of modes, modes interlacing, mode splitting due to edges, and others [7]- [11]. One of the main limiting factors is the phenomenon of dispersion, which means that the velocity of waves varies depending on the frequency ( f ) and the object thickness (d) [12]. Velocity as a function of frequency determines the occurrence of two-phase and group Manuscript received July 14, 2021; revised October 26, 2021; accepted November 3, 2021.…”

Section: Introductionmentioning

confidence: 99%

The Methodology for the Reliability Evaluation of the Signal Processing Methods Used for the Dispersion Estimation of Lamb Waves

Draudvilienė

Meškuotienė

2022

IEEE Trans. Instrum. Meas.

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The applications of ultrasonic Lamb waves are becoming more and more frequent and diverse in industrial fields. These waves are used in non-destructive testing (NDT), structural health monitoring (SHM), for the assessment of the quality of materials, etc. However, due to the unusual properties of these waves, new or adapted signal processing methods are necessary to use for the analysis of such wave signals. Based on the requirements of ISO 17025, the work presents the methodology for verification of the signal processing methods used to reconstruct the dispersion curves of the phase and group velocities of Lamb waves. The key sequence of the mathematical and experimental stages, which must be passed to evaluate the reliability of the methods are developed. The present methodology includes the algorithm to optimally quantify the uncertainty, as to avoid additional testing, saving cost and time. The main characteristics and sources of the uncertainties, that mainly affect the accuracy of the obtained results are identified, analyzed, and presented. New standards for certification testing, inspection, and monitoring can be developed more easily and quickly based on the provided methodology in the future.

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“…The above signal changes provide a lot of information for damage monitoring. The crack monitoring methods usually establish the relationship between crack length and signal features, such as wavelet transform [13], time of flight (ToF) [14][15], probability reconstruction algorithm [16][17]. In addition, some advanced algorithms, such as Bayesian method [18] and particle filter [19], have been used to predict the trend of crack growth.…”

Section: Introductionmentioning

confidence: 99%

A Cross-Scanning Crack Damage Quantitative Monitoring and Imaging Method

Wang

Zhang

et al. 2022

IEEE Trans. Instrum. Meas.

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Multihelical Lamb Wave Imaging for Pipe-Like Structures Based on a Probabilistic Reconstruction Approach

Abstract: 2020) 'Multi-helical lamb wave imaging for pipe-like structures based on a probabilistic reconstruction approach.', IEEE Transactions on Instrumentation and Measurement, 70 .

Cited by 14 publications

References 41 publications

Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme

Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme

The Methodology for the Reliability Evaluation of the Signal Processing Methods Used for the Dispersion Estimation of Lamb Waves

A Cross-Scanning Crack Damage Quantitative Monitoring and Imaging Method

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