Corrosion detection with ray-based and full-waveform guided wave tomography

2020 ◽  
Author(s):  
Min Lin ◽  
Caleb Wilkins ◽  
Jing Rao ◽  
Zheng Fan ◽  
Yang Liu
Keyword(s):  
Guided Wave ◽  
Corrosion Detection ◽  
Full Waveform ◽  
Wave Tomography

scholarly journals Passive SHM System for Corrosion Detection by Guided Wave Tomography

2017 ◽  
pp. 21-29 ◽  
Author(s):  
Tom Druet ◽  
Bastien Chapuis ◽  
Manfred Jules ◽  
Guillaume Laffont ◽  
Emmanuel Moulin
Keyword(s):  
Guided Wave ◽  
Corrosion Detection ◽  
Wave Tomography

Robust Guided Wave Tomography Method for Large and Irregular Defects

2021 ◽  
Author(s):  
Junkai Tong ◽  
Min Lin ◽  
Xiaocen Wang ◽  
Jiahao Ren ◽  
Jian Li ◽  
...  
Keyword(s):  
Complex Shape ◽  
Waveform Inversion ◽  
Guided Wave ◽  
Diffraction Tomography ◽  
Multiple Defects ◽  
Full Waveform ◽  
Speed Advantage ◽  
Wave Tomography ◽  
Tomography Method ◽  
Defect Imaging

Abstract Finding a fast, robust way to quantitatively measuring the remaining wall thickness of complex structures when multiple defects exist is one of the leading challenges in Nondestructive Testing (NDT). Traditional inversion algorithms like ray tomography and full waveform inversion (FWI) suffered from problems like convergence, limited resolution and slow speed. Diffraction tomography (DT) has speed advantage over the preceding methods and its resolution can be further amplified by integrating with other methods like bent-ray tomography and iteration. However, DT can only detect shallow and small defects. Compared with those methods, convolutional neural network (CNN) opens a new way for quantitative defect imaging, as with pre-trained data it can achieve significant speed and resolution than the traditional methods. In this paper, we investigated the performance of CNN in imaging multiple defects and the inversion results show that when dealing with multiple defects with complex shape on a plate-like structure, CNN can achieve better resolution than other methods with maximum errors below 0.54mm in most regions. This research provides the experimental guidance for future study in finding the possible ways to improve the resolution of the algorithms.

Accurate Thickness Inversion of Corrosion Using A1 Lamb Wave

2021 ◽  
Author(s):  
Min Lin ◽  
Yang Liu
Keyword(s):  
High Resolution ◽  
Oil And Gas ◽  
Residual Life ◽  
Early Stage ◽  
Corrosion Damage ◽  
Oil And Gas Industry ◽  
Forward Modeling ◽  
Guided Wave ◽  
Velocity Inversion ◽  
Wave Tomography

Abstract Corrosion is one of the most critical issues in the oil and gas industry, leading to severe environmental and economic problems. Due to the high cost and serious safety risk of corrosion, it is essential to improve current corrosion testing techniques to detect corrosion damages at an early stage. Guided wave tomography (GWT) demonstrates its great potential to inspect and quantify the corrosion damage. GWT is capable of determining the residual life of corrosion structures by quantifying the remaining wall thickness. In this paper, an accurate guided wave tomography technique incorporating full waveform inversion (FWI) and higher-order Lamb waves (A1 mode) is presented for plate-like structures, which is able to get high-resolution reconstruction results. The technique consists of three steps: forward modeling, velocity inversion and thickness reconstruction. The forward modeling is computed by solving the elastic full-wave equations in 2-D time domain by using the finite difference method. High-resolution phase velocity inversion can then be obtained by minimizing the waveform misfit function between simulated and recorded data using a second order optimization method, which updates the velocity model from low to high frequencies iteratively. Finally, the velocity variations can be transformed into depth profiles by using the dispersive characteristics of ultrasonic guided waves; therefore, the thickness reconstruction can be obtained. The numerical simulations are performed on an aluminum plate with a complicated corrosion defect. By comparing the thickness reconstruction maps using both A1 and A0 modes, the results demonstrate that FWI with A1 mode can achieve significantly better resolution of corrosion imaging than that with A0 mode.

Field trials results of guided wave tomography

2015 ◽  
Author(s):  
Arno Volker ◽  
Tim van Zon ◽  
Edwin van der Leden
Keyword(s):  
Field Trials ◽  
Guided Wave ◽  
Wave Tomography
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