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

Shengping Li, Jie Zhang, Gaofei Liu, Nanhui Chen, Lulu Tian, Libing Bai, Cong Chen

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Shengping LiSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0000-0003-3779-9461

Jie ZhangSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Gaofei LiuChina Petroleum Pipeline Insptection Technologies Co., Ltd., Langfang 065000, China.

Nanhui ChenSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Lulu TianSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Libing BaiSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0000-0001-8906-0576

Cong ChenSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Funding

National Natural Science Foundation of China U2030205, 62003075, 61903065, 62003074Sichuan Science and Technology Planning Project 2022JDJQ0040

6 · The paper itself

Abstract

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.

Indexed as

image registrationMagnetic Flux Leakagemutual imformationnondestructive testingPSOsolenoid modal

Identifiers

PMID36673307

DOI10.3390/e25010167

PMCPMC9858165

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.