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Author:

Yang, G. (Yang, G..) | Liu, D. (Liu, D..) | Zeng, K. (Zeng, K..) | Liu, Z. (Liu, Z..) | Cheng, J. (Cheng, J..) | Zheng, Y. (Zheng, Y..) | Zou, D. (Zou, D..) | Zhou, J. (Zhou, J..) | Liu, R. (Liu, R..) | Tian, G. (Tian, G..) | Gao, B. (Gao, B..)

Indexed by:

EI Scopus SCIE

Abstract:

The minimal lattice changes caused by thermal ageing present a significant challenge for non-destructive testing. This study proposes the use of a high-frequency resonance eddy current sensor and a multi-physical field fusion method to address this issue. Initially, high-frequency resonance technology is employed, whereby not only is an eddy current secondary magnetic field generated, but also an electric field in the gap between the planar coil and the metal. Therefore, the excitation of a multi-physical field in eddy current sensors has been achieved. Secondly, a probe multi-parameter separation algorithm is proposed. Consequently, the separation of the magnetic and electric fields can be achieved. The results of experiments conducted on 12CrMoV steel demonstrate that the parameter capacitance relating to electric fields is more accurate and linear than the parameters resistance and inductance relating to eddy current secondary magnetic fields. Finally, the multi-parameter and multi-physical field fusion method is discussed in order to enhance the accuracy of thermal ageing characterization. The results of the experiments demonstrate that the fusion characterization method, which combines resistance and capacitance, leads to a significant reduction in error, by as much as 80%, when applied to the characterization of eddy current magnetic fields and gap electric fields.  © 2001-2012 IEEE.

Keyword:

High-frequency resonance eddy current sensor thermal aging characterization multi-physical field fusion 12CrMoV nondestructive testing

Author Community:

  • [ 1 ] [Yang G.]University of Electronic Science and Technology of China, School of Automation Engineering, Sichuan, Chengdu, 611731, China
  • [ 2 ] [Liu D.]University of Electronic Science and Technology of China, School of Automation Engineering, Sichuan, Chengdu, 611731, China
  • [ 3 ] [Zeng K.]Dongfang Boiler Co., Ltd, Sichuan, Deyang, 618000, China
  • [ 4 ] [Liu Z.]Beijing University of Technology, Faculty of Materials and Manufacturing, Beijing, 100124, China
  • [ 5 ] [Cheng J.]Beijing University of Technology, College of Mechanical and Energy Engineering, Beijing, 100124, China
  • [ 6 ] [Zheng Y.]China Special Equipment Inspection and Research Institute, Beijing, China
  • [ 7 ] [Zou D.]University of Electronic Science and Technology of China, School of Automation Engineering, Sichuan, Chengdu, 611731, China
  • [ 8 ] [Zhou J.]University of Electronic Science and Technology of China, School of Automation Engineering, Sichuan, Chengdu, 611731, China
  • [ 9 ] [Liu R.]University of Electronic Science and Technology of China, School of Automation Engineering, Sichuan, Chengdu, 611731, China
  • [ 10 ] [Tian G.]Newcastle University, School of Engineering, Newcastle Upon Tyne, NE1 7RU, United Kingdom
  • [ 11 ] [Gao B.]University of Electronic Science and Technology of China, School of Automation Engineering, Sichuan, Chengdu, 611731, China

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Source :

IEEE Sensors Journal

ISSN: 1530-437X

Year: 2025

4 . 3 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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