Automated Box Data Matching for Multi-Modal Magnetic Flux Leakage Inspection of Pipelines

Peng, Xiang; Liu, Huan; Siggers, Kevin; Liu, Zheng

doi:10.1109/tmag.2021.3061060

Cited by 9 publications

(1 citation statement)

References 21 publications

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“…Magnetic Flux Leakage (MFL) detection is widely used in the nondestructive testing of defects in ferromagnetic components [1][2][3][4]. The inversion for the profile of a defect is the most interesting part of the related research.…”

Section: Introductionmentioning

confidence: 99%

Image Registration for Visualizing Magnetic Flux Leakage Testing under Different Orientations of Magnetization

Zhang

Liu

et al. 2023

Entropy

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The Magnetic Flux Leakage (MFL) visualization technique is widely used in the surface defect inspection of ferromagnetic materials. However, the information of the images detected through the MFL method is incomplete when the defect (especially for the cracks) is complex, and some information would be lost when magnetized unidirectionally. Then, the multidirectional magnetization method is proposed to fuse the images detected under different magnetization orientations. It causes a critical problem: the existing image registration methods cannot be applied to align the images because the images are different when detected under different magnetization orientations. This study presents a novel image registration method for MFL visualization to solve this problem. In order to evaluate the registration, and to fuse the information detected in different directions, the mutual information between the reference image and the MFL image calculated by the forward model is designed as a measure. Furthermore, Particle Swarm Optimization (PSO) is used to optimize the registration process. The comparative experimental results demonstrate that this method has a higher registration accuracy for the MFL images of complex cracks than the existing methods.

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Section: Introductionmentioning

confidence: 99%