Research on Dynamic Detection of Rail Rolling Contact Fatigue Crack Based on Eddy Current Thermography

被引：0

作者：

Miao L. ^{[1
]}

Gao B. ^{[1
]}

Shi Y. ^{[2
]}

Li H. ^{[1
]}

Li X. ^{[1
]}

Wu T. ^{[1
]}

Zhang X. ^{[1
]}

Tian G. ^{[1
,3
]}

机构：

[1] School of Automation Engineering, University of Electronic Science and Technology, Chengdu

[2] Railway Infrastructure Inspection Center, CHINA RAILWAY, Beijing

[3] School of Electrical and Electronic Engineering, Newcastle University, Newcastle

来源：

Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2021年 / 57卷 / 18期

关键词：

Eddy current thermography; Low-speed inspection; Quantitative detection; Rolling contact fatigue crack; Sensor architecture;

D O I：

10.3901/JME.2021.18.086

中图分类号：

学科分类号：

摘要：

In response to the challenge of rail rolling contact fatigue crack detection, a multi-physics eddy current thermography technology under new sensor structures is proposed. Through COMSOL Multiphysics finite element simulation software, the electromagnetic field characteristics of the cylindrical magnetic core structure, the arc-shaped yoke structure and the U-shaped yoke structure are analysed, and the detection effect of fatigue crack under different sensing architectures is studied. According to actual application conditions, the L-shaped yoke and the shuttle-shaped yoke structures are developed based on the U-shaped yoke structure, and the induction excitation source system is integrated and developed. Defect detection experiment of milled rail test blocks in the static state shows that the self-developed system has high detection sensitivity for small defects on the rail surface. It can realize quantitative analysis of 0.5 mm wide defects and identify defects with a minimum width of 0.2 mm on the rail surface. Through the defect detection experiment of disc, the fatigue crack detection under speed effect is studied. The proposed robust low-rank tensor crack decomposition algorithm greatly eliminates the background noise of the original thermal image and improves the defect detection resolution. Finally, the low-speed rail inspection experimental platform is built and integrated to verify effectiveness of complex rolling contact fatigue crack detection on rail treads. © 2021 Journal of Mechanical Engineering.

引用

页码：86 / 97

页数：11

共 28 条

[1]

TIAN Guiyun, GAO Bin, GAO Yunlai, Et al., Review of railway rail defect non-destructive testing and monitoring, Chinese Journal of Scientific Instrument, 37, 8, pp. 1763-1780, (2016)

[2]

YU Rongquan, LI Qiang, LI Na, Et al., Numerical analysis on prediction of rolling contact fatigue crack initiation life of wheel, Journal of the China Railway Society, 37, 12, pp. 20-24, (2015)

[3]

WANG Zhe, Crack propagation analysis of wheel/rail rolling contact fatigue on high speed railway, (2019)

[4]

PAPAELIAS M, ROBERTS C, DAVIS C L., A review on non-destructive evaluation of rails: State-of-the-art and future development, Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit, 222, 4, pp. 367-384, (2008)

[5]

HU Songtao, SHI Wenze, LU Chao, Et al., Research on rapid imaging detection of electromagnetic ultrasonic surface wave synchrosqueezed wavelet for rail tread cracks, Chinese Journal of Scientific Instrument, 41, 1, pp. 35-46, (2020)

[6]

MANEESH K M, MUTHU S M, SARANYA M, Et al., A survey on crack detection technique in railway track, 2018 Conference on Emerging Devices and Smart Systems (ICEDSS), pp. 269-272, (2018)

[7]

JIA Yinliang, LIANG Kangwu, WANG Ping, Et al., Enhancement method of magnetic flux leakage signals for rail track surface defect detection, IET Science, Measurement & Technology, 14, 6, pp. 711-717, (2020)

[8]

GAO Yunlai, WANG Ping, TIAN Guiyun, Et al., High-speed online inspection techniques of rail crack defects based on electromagnetic Principle, NDT, 34, 12, pp. 1-11, (2012)

[9]

SHEN J, ZHOU L, ROWSHANDEL H, Et al., Prediction of RCF clustered cracks dimensions using an ACFM sensor and influence of crack length and vertical angle, Nondestructive Testing And Evaluation, 35, 1, pp. 1-18, (2019)

[10]

ZHANG Hui, JIN Xiating, HE Zhendong, Et al., Automatic visual detection method of railway surface defects based on curvature filtering and improved GMM, Chinese Journal of Scientific Instrument, 39, 4, pp. 181-194, (2018)

← 1 2 3 →