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

Lin, Min; Wilkins, Caleb; Rao, Jing; Fan, Zheng; Liu, Yang

doi:10.1117/12.2561178

Cited by 5 publications

(5 citation statements)

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“…The results from the latest objective function will be substituted into Equation (7). The solution gradually converges to stability after several iterations between Equations ( 7) and (8). In brief, according to Born approximation, the initial total field can be replaced by the incident field, and the objective function will be updated by several repeated iterations.…”

Section: Establishment Of the Algorithmmentioning

confidence: 99%

“…During the method development, the algorithm plays an important role in final defect visualization, which is directly related to the quality of final imaging. The defect profile is required to be reconstructed after utilizing a proper algorithm based on the wave amplitude, 8,9 phase, 10,11 wave number, 12,13 and other related characteristics of received signals from transducers. Therefore, how to develop a new algorithm and establish an accurate mathematical model to realize the qualitative and quantitative analysis according to different conditions, is of great significance for NDT or SHM.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A novel wave tomography method for defect reconstruction with various arrays

Qian

Wang

Zhang

et al. 2023

Structural Health Monitoring

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In order to reconstruct the possible defects on the plate surface with arrays, a new wave tomography method based on the method of moments is established in this paper. According to the relationship between the probe number and grid amount, two algorithms, that is, the neural network and principal component analysis (PCA), are proposed and used to solve the ill-conditioned inversion equations. The neural network makes imaging feasible even if input data are not enough, and the PCA can greatly improve the computational efficiency via reducing the matrix dimension. Both numerical simulations and experimental measurements are conducted with the algorithm’s correctness and high precision validated. After investigating the influence of probe number on imaging quality, it is demonstrated that the algorithm can exactly predict the defect location when the input scattering data is not enough or fewer probes are arranged. More probes are needed for reconstructing the specific shape and thickness, especially when multiple defects are included. The qualitative results and quantitative data are conducive to providing some reference for engineering applications in nondestructive testing and structural health monitoring.

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Section: Establishment Of the Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel wave tomography method for defect reconstruction with various arrays

Qian

Wang

Zhang

et al. 2023

Structural Health Monitoring

View full text Add to dashboard Cite

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“…The FWI is an imaging technology extensively used in the geophysics community and recently introduced into medical imaging [32]. Guasch et al successfully generated accurate 2D and 3D brain tomography images with sub-millimeter resolution using wavefield simulation data based on FWI [33].…”

Section: Introductionmentioning

confidence: 99%

3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks

Ren,

Wang,

Liu

et al. 2023

Sensors

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Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hindered by the high acoustic impedance contrast between the skull and soft tissue. This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and deep learning for precise brain ultrasound reconstruction. We constructed a network comprising one input layer, four convolution layers, and one pooling layer to train our algorithm. In the simulation experiment, the Pearson correlation coefficient between the reconstructed and true images was exceptionally high. In the laboratory, the results showed a slightly lower but still impressive coincidence degree for 3D reconstruction, with pure water serving as the initial model and no prior information required. The 3D network can be trained in 8 h, and 10 samples can be reconstructed in just 12.67 s. The proposed 3D BIFCN algorithm provides a highly accurate and efficient solution for mapping wavefield frequency domain data to 3D brain models, enabling fast and precise brain tissue imaging. Moreover, the frequency shift phenomenon of blood may become a hallmark of BIFCN learning, offering valuable quantitative information for whole-brain blood imaging.

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“…In general, approximate 2D forward models are preferred over exact 3D models, due to their simplicity, low computational cost, feasibility of combining with tomographic algorithms, and their capability to evaluate the thickness of the waveguides from the velocity. Furthermore, the majority of research on GWT has focused on simple geometries, such as flat plates [29][30][31][32] and straight pipes [33][34][35]. However, only a few studies have investigated the application of GWT to pipe bends.…”

Section: Introductionmentioning

confidence: 99%

Acoustic Forward Model for Guided Wave Propagation and Scattering in a Pipe Bend

Rasgado-Moreno

Rist

Land

et al. 2022

Sensors

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The sections of pipe bends are hot spots for wall thinning due to accelerated corrosion by fluid flow. Conventionally, the thickness of a bend wall is evaluated by local point-by-point ultrasonic measurement, which is slow and costly. Guided wave tomography is an attractive method that enables the monitoring of a whole bend area by processing the waves excited and received by transducer arrays. The main challenge associated with the tomography of the bend is the development of an appropriate forward model, which should simply and efficiently handle the wave propagation in a complex bend model. In this study, we developed a two-dimensional (2D) acoustic forward model to replace the complex three-dimensional (3D) bend domain with a rectangular domain that is made artificially anisotropic by using Thomsen parameters. Thomsen parameters allow the consideration of the directional dependence of the velocity of the wave in the model. Good agreement was found between predictions and experiments performed on a 220 mm diameter (d) pipe with 1.5d bend radius, including the wave-field focusing effect and the steering effect of scattered wave-fields from defects.

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

Cited by 5 publications

References 0 publications

A novel wave tomography method for defect reconstruction with various arrays

A novel wave tomography method for defect reconstruction with various arrays

3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks

Acoustic Forward Model for Guided Wave Propagation and Scattering in a Pipe Bend

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