Research on eddy current testing and defect evaluation methods for complex cracks

被引：0
|
作者：
Jin J. [1 ]
Zhang Q. [1 ]
Han B. [1 ]
Yang S. [1 ]
Ren Y. [2 ]
机构：
[1] College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing
[2] Special Equipment Safety Supervision Inspection Institute of Jiangsu Province, Nanjing
来源：
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2024年 / 45卷 / 02期
关键词：
eddy current testing; feature extraction; radial basis function neural network; rolling contact fatigue; wireless power transfer;
D O I：
10.19650/j.cnki.cjsi.J2312068
中图分类号：
学科分类号：
摘要：
The rolling contact fatigue cracks on the rail surface and upper surface usually exist in the form of inclined cracks or multiangle complex cracks, which are difficult to detect and evaluate. Based on this, the wireless power transfer-eddy current testing (WPT-ECT) is adopted. A new probe structure is designed, and neural network algorithms are combined to detect and evaluate cracks. Firstly, different from the existing wireless power transfer-eddy current testing methods, the resonant circuit is constructed by increasing the excitation frequency instead of the series-parallel capacitance. Secondly, according to the characteristics of complex cracks, a directional probe structure consisting of two eight-figure excitation coils and two rectangular receiving coils is designed. Finally, the features of the detected signal are fully extracted, and the cracks are identified by the radial basis function neural network algorithm. Simulation and experimental results show that the proposed probe structure is sensitive to defects at any angle. Meanwhile, the recognition accuracy of the radial basis function algorithm for oblique crack, T crack, Y crack, and T crack with 1. 2 mm lift-off is 92. 00%, 95. 27%, 96. 64%, and 89. 50%, respectively. © 2024 Science Press. All rights reserved.
引用
收藏
页码：280 / 288
页数：8
相关论文
共 23 条
  • [11] DONG H R, QI P, HAN J, Et al., High-resolution magnetic imaging probe with staggered sensor arrays for small defects inspection, IEEE Sensors Journal, 23, 17, pp. 19153-19162, (2023)
  • [12] XU P, LIU B L, CHEN Y X., Detection method of rail cracks based on differential flexible eddy current probe, China Mechanical Engineering, 34, 20, pp. 2419-2427, (2023)
  • [13] YANG R, ZHAI G F, XU B, Et al., Design of flexible planar differential probe based on pulsed eddy current technology, Instrument Technique and Sensor, 10, pp. 1-5, (2022)
  • [14] HE Y Z., Research on new method of defect identification and evaluation in electromagnetic nondestructive testing, (2014)
  • [15] SUN F SH, FAN M B, CAO B H, Et al., Accurate THz thickness measurement method of thermal barrier coating based on time-frequency key information fusion, Journal of Mechanical Engineering, 59, 14, pp. 10-22, (2023)
  • [16] LIANG X B., Research on intelligent diagnosis and risk assessment method of natural gas pipeline defects, (2020)
  • [17] YAN Y, LIU Y, ZHU J ZH, Et al., Quantitative evaluation of rail natural cracks based on the characteristics of eddy current pulse thermal imaging, Journal of Mechanical Engineering, 57, 18, pp. 75-85, (2021)
  • [18] ZHAO L Q., Research on detection and identification of rail wear condition based on train vibration information, (2021)
  • [19] ABER C, HAMID A, ELCHIKH M, Et al., Eddy current microsensor and RBF neural networks for detection and characterization of small surface defects, Measurement Science Review, 22, 3, pp. 112-121, (2022)
  • [20] LIU J W, FRANCIS D., Characterizations of high frequency planar transformer with a novel comb-shaped shield, IEEE Transactions on Magnetics, 47, 10, pp. 4493-4496, (2011)
123