Defect Width Assessment Based on the Near-Field Magnetic Flux Leakage Method.

Erlong Li, Yiming Chen, Xiaotian Chen, Jianbo Wu
Author Information
  1. Erlong Li: School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
  2. Yiming Chen: School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
  3. Xiaotian Chen: School of Electrical & Electronic Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
  4. Jianbo Wu: School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.

Abstract

Magnetic flux leakage (MFL) testing has been widely used as a non-destructive testing method for various materials. However, it is difficult to separate the influences of the defect geometrical parameters such as depth, width, and length on the received leakage signals. In this paper, a "near-field" MFL method is proposed to quantify defect widths. Both the finite element modelling (FEM) and experimental studies are carried out to investigate the performance of the proposed method. It is found that that the distance between two peaks of the "near-field" MFL is strongly related to the defect width and lift-off value, whereas it is slightly affected by the defect depth. Based on this phenomenon, a defect width assessment relying on the "near-field" MFL method is proposed. Results show that relative judging errors are less than 5%. In addition, the analytical expression of the "near-field" MFL is also developed.

Keywords

References

Sensors (Basel). 2014 Sep 04;14(9):16454-66 [PMID: 25192314]
Sensors (Basel). 2021 Jan 19;21(2): [PMID: 33477948]
Sensors (Basel). 2021 May 13;21(10): [PMID: 34068412]
Sensors (Basel). 2021 Jun 03;21(11): [PMID: 34205033]

Grants

  1. 51907131/National Natural Science Foundation of China
  2. 52005510/National Natural Science Foundation of China
  3. 2060114/National Key Research and Development Program of China
  4. 2020JDRC0060/Sichuan Province Science and Technology Support Program
  5. 20ZDYF2964/Sichuan Province Science and Technology Support Program
  6. 2021YFG0203/Sichuan Province Science and Technology Support Program
  7. 2021SCU12145/Science Foundation for Excellent Youth Scholars of Sichuan University

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