Article Article
Quantitative Stress Evaluation and Defect Identification in Ferromagnetic Steels Based on Residual Magnetic Field Measurements

In this paper, the correlation between the residual magnetic field (RMF) and the applied load is investigated. Tensile tests were carried out to measure RMF signals on the surface of 30CrNiMo8 steel specimens with three types of machined defect shapes. Results show that the RMF curves of the three different defective specimens demonstrate similar overall evolution patterns during the loading process, while the magnetic signals exhibit noticeable differences in the defect area. It suggests that the profiles of the stress-induced RMF curves are strongly dependent on the defect’s shape, notch width, and load level. An improved method is proposed to extract some quantitative characteristic parameters from the magnetic signals. The characteristic parameters that reflect the fluctuation degree are in quadratic polynomial relation with the applied load, which can be potentially used to evaluate the applied load acting on a ferromagnetic material with a macro defect. The characteristic parameters that reflect the acting range seem to be independent of the applied load, and the normal ones are capable of capturing the defect’s location and shape. This paper presents a supplement for quantitative defect identification for discontinuities in ferromagnetic steels by RMF measurements.



Bao, S., M. Fu, H. Lou, and S. Bai, 2017a, “Defect Identification in Ferromagnetic Steel Based on Residual Magnetic Field Measurements,” Journal of Magnetism and Magnetic Materials, Vol. 441, pp. 590–597, /10.1016/j.jmmm.2017.06.056.

Bao, S., M. Fu, S. Hu, Y. Gu, and H. Lou, 2016a, “A Review of the Metal Magnetic Memory Technique,” Proceedings of the ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering, Vol. 4: Materials Technology, Busan, South Korea, 19–24 June, /OMAE2016-54269.

Bao, S., M. Fu, Y. Gu, and H. Lou, 2017b, “Quantitative Characterization of Stress Concentration of Low-Carbon Steel by Metal Magnetic Memory Testing,” Materials Evaluation, Vol. 75, No. 3, pp. 397–405.

Bao, S., M.L. Fu, H.J. Lou, S.Z. Bai, and S.N. Hu, 2016b, “Evaluation of Stress Concentration of a Lowcarbon Steel Based on Residual Magnetic Field Measurements,” Insight, Vol. 58, No. 12, pp. 678–682,

Chen, H., C. Wang, and X. Zuo, 2017, “Research on Methods of Defect Classification Based on Metal Magnetic Memory,” NDT&E International, Vol. 92, pp. 82–87,

Dong, L., B. Xu, S. Dong, Q. Chen, and W. Dan, 2008, “Monitoring Fatigue Crack Propagation of Ferromagnetic Materials with Spontaneous Abnormal Magnetic Signals,” International Journal of Fatigue, Vol. 30, No. 9, pp. 1599–1605,

Huang, H., S. Jiang, C. Yang, and Z. Liu, 2014, “Stress Concentration Impact on the Magnetic Memory Signal of Ferromagnetic Structural Steel,” Nondestructive Testing and Evaluation, Vol. 29, No. 4, pp. 377–390,

Li, C., D. Lihong, W. Haidou, L. Guolu, and X. Binshi, 2016, “Metal Magnetic Memory Technique Used to Predict the Fatigue Crack Propagation Behavior of 0.45%C Steel,” Journal of Magnetism and Magnetic Materials, Vol. 405, pp. 150–157, /10.1016/j.jmmm.2015.12.035.

Li, L., H. Songling, W. Xiaofeng, S. Keren, and W. Su, 2003, “Magnetic Field Abnormality Caused by Welding Residual Stress,” Journal of Magnetism and Magnetic Materials, Vol. 261, No. 3, pp. 385–391,

Mandal, K., Th. Cramer, and D.L. Atherton, 2000, “The Study of a Racetrack-Shaped Defect in Ferromagnetic Steel by Magnetic Barkhausen Noise and Flux Leakage Measurements,” Journal of Magnetism and Magnetic Materials, Vol. 212, Nos. 1–2, pp. 231–239, /10.1016/S0304-8853(99)00595-8.

Roskosz, M., and P. Gawrilenko, 2008, “Analysis of Changes in Residual Magnetic Field in Loaded Notched Samples,” NDT&E International, Vol. 41, No. 7, pp. 570–576,

Shi, C., D. Shiyun, X. Binshi, and H. Peng, 2010, “Stress Concentration Degree Affects Spontaneous Magnetic Signals of Ferromagnetic Steel Under Dynamic Tension Load,” NDT&E International, Vol. 43, No. 1, pp. 8–12,

Shi, P., K. Jin, and X. Zheng, 2017, “A Magnetomechanical Model for the Magnetic Memory Method,” International Journal of Mechanical Sciences, Vols. 124–125, pp. 229–241, .2017.03.001.

Wang, Z.D., K. Yao, B. Deng, and K.Q. Ding, 2010a, “Quantitative Study of Metal Magnetic Memory Signal Versus Local Stress Concentration,” NDT&E International, Vol. 43, No. 6, pp. 513–518, /10.1016/j.ndteint.2010.05.007.

Wang, Z.D., K. Yao, B. Deng, and K.Q. Ding, 2010b, “Theoretical Studies of Metal Magnetic Memory Technique on Magnetic Flux Leakage Signals,” NDT&E International, Vol. 43, No. 4, pp. 354–359, /10.1016/j.ndteint.2009.12.006.

Wilson, J.W., G.Y. Tian, and S. Barrans, 2007, “Residual Magnetic Field Sensing for Stress Measurement,” Sensors and Actuators A: Physical, Vol. 135, No. 2, pp. 381–387,

Yao, K., K. Shen, Z.-D. Wang, and Y.-S. Wang, 2014, “Three-Dimensional Finite Element Analysis of Residual Magnetic Field for Ferromagnets Under Early Damage,” Journal of Magnetism and Magnetic Materials, Vol. 354, pp. 112–118,

Zhong, L., L. Li, and X. Chen, 2013, “Simulation of Magnetic Field Abnormalities Caused by Stress,” IEEE Transactions on Magnetics, Vol. 49, No. 3, pp. 1128–1134,


Usage Shares
Total Views
205 Page Views
Total Shares
0 Tweets
0 PDF Downloads
0 Facebook Shares
Total Usage