Dynamic Rail Near-Surface Inspection of Multiphysical Coupled Electromagnetic and Thermography Sensing System

Li, Haoran, Gao, Bin, Lu, Xiaolong, Zhang, Xiyuan, Shi, Yunhan, Ru, Gaige and Woo, Wai Lok (2023) Dynamic Rail Near-Surface Inspection of Multiphysical Coupled Electromagnetic and Thermography Sensing System. IEEE Transactions on Instrumentation and Measurement, 72. p. 3501613. ISSN 0018-9456

Dynamic Rail Near-surface Inspection of Multi-physical Coupled Electromagnetic and Thermography Sensing System-Final.pdf - Accepted Version

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Official URL: https://doi.org/10.1109/tim.2022.3224531


The effectiveness of railway fault inspection has remained challenging. Conventional techniques are still functionally limited and unable to meet the increasing demand of railway diagnosis. To mitigate the variety of rail fault detection problems, this article proposes a dynamic railway inspection system based on multiphysical coupled electromagnetic and thermography sensing. It further shows the development and construction of a new inverted L-type magnet yoke abreast with volumetric coil array. The novel structure can not only significantly enhance the sensitivity and detectability of the region of interest (ROI), but also effectively detect the subsurface defects with the compensation of coils array due to the coupled electromagnetic field. Furthermore, the theoretical analysis of the coupled physical fields has been derived and proved to be consistent with the numerical simulation results. A rail test sample with various defects is carried out to verify the feasibility of the proposed system. Additionally, a metric learning post-processing algorithm has been conducted for distilling eddy current signals and thermograms to improve the accuracy of the detection results. On-site experimental and contrast results with various levels of performance validation have demonstrated that the integrated system is well suited for dynamic rail inspection on near-surface cracks at speed of 1 km/h.

Item Type: Article
Additional Information: Funding information: The work was supported in part by the National Natural Science Foundation of China under Grant 61971093, Grant 61527803, and Grant 61960206010; in part by the Science and Technology Department of Sichuan, China under Grant 2019YJ0208, Grant 2018JY0655, and Grant 2018GZ0047; and in part by the Fundamental Research Funds for the Central Universities Grant ZYGX2019J067.
Uncontrolled Keywords: Anomaly detection, dynamic defect detection, multiphysical coupled sensing, railway fault diagnosis
Subjects: F300 Physics
G600 Software Engineering
H200 Civil Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 27 Jan 2023 08:25
Last Modified: 27 Jan 2023 08:30
URI: https://nrl.northumbria.ac.uk/id/eprint/51251

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