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Updated: Jan 17, 2026

Quantifying the Relative Thickness of Conductive Ferromagnetic Materials Using Detector Coil-Based Pulsed Eddy Current Sensors
Published on: January 16, 2020
Research on Quantitative Evaluation of Defects in Ferromagnetic Materials Based on Electromagnetic Non-Destructive
Xiangyi Hu1, Ruijie Xie1, Ruotian Wang1
1School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China.
Abstract:
Defects are a direct cause of failure in ferromagnetic components, which can be evaluated via electromagnetic non-destructive testing (ENDT) methods. However, the existing studies exhibit several limitations (e.g., inaccurate quantification, over-reliance on algorithms, and non-intuitive result presentation, among others) in quantitative defect evaluation. To accurately describe the quantitative relationship between ENDT signals and defect dimensional parameters, the electromagnetic model and electromagnetic induction model are introduced in this paper to elucidate the physical mechanism of ENDT, as both models provide a basis for the selection of the constitutive relationship for simulation analysis. Then, a higher precision three-dimensional nonlinear finite element simulation model is established, and the effects of the excitation parameters and detection positions on signal characteristics are investigated. The simulation results indicate that the excitation frequency influences both the detection depth and sensitivity of ENDT, while the voltage amplitude affects the peak strength of the magnetic signal. Consequently, the excitation parameters are determined to be a 10 Hz frequency with a 25 V amplitude. Based on the characterization of signal peaks at positions of 0°, 90°, 180°, and 270°, the characteristic parameter KA of the peak electrical signal curve is proposed as a quantitative index for evaluating defects. The quantitative experimental results show that KA is related to the defect dimension. Specifically, the KA value monotonically decreases from a constant greater than 1 to a constant less than 1 as the defect length increases, KA is positively correlated with the defect width, and KA follows a parabolic trend (first increase and then decrease) as the defect depth increases. Notably, KA values associated with defect width and depth remain below 1. All the above findings provide a basis for evaluating defect dimensions. The results of this paper provide a novel ENDT method for evaluating defects, which is of great significance for improving the accuracy of ENDT and promoting its engineering applications.
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