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An Auto-Calibration Algorithm for Hybrid Guided Wave Tomography Based on Full Waveform Inversion

Authors :
Jiawei Wen
Can Jiang
Yubing Li
Hao Chen
Weiwei Ma
Jian Wang
Source :
IEEE Access, Vol 11, Pp 62496-62509 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

Combining with the dispersion characteristics of ultrasonic guided waves, full waveform inversion method shows great application potential in the quantificational detections of defects in plate- and pipe- like structures. Owing to the inversion efficiency problem, the forward modeling is generally based on the acoustic equation approximation, and a reference signal unaffected by the defects needs to be artificially selected to correct the approximation forward simulation results. This study presents an auto-calibration (without artificial selection of the reference signal) and high-precision imaging method based on the combination of the full waveform inversion and ray tomography algorithm. The ray tomography results are not only used to automatically select the reference signal based on an auto-calibration process, but also used as the macro initial model for the full waveform inversion method, which decreases the possibility of losing in local minimum values during the inversion process and enhances the robustness of the inversion method. Therefore, compared with the classical guided wave tomography method based on full waveform inversion, relatively high-frequency transducers can be used to acquire high-frequency signals, and thus, the imaging accuracy could be effectively improved. Simulation and experiment results have verified that the global relative error of the auto-calibration method is smaller than the classical method. The good imaging results of irregular complex defects confirmed the effectiveness and applicability of the new method.

Details

Language :
English
ISSN :
21693536
Volume :
11
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.790f7efcc344dbb1a4563ceb390aac
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2023.3287646