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Study on the Judgment of Fatigue Damage Stages in Welds Based on Entropy Analysis

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Abstract

This study aims to explore the relationship between the weld fatigue stages and metal magnetic memory signals so as to address challenges in detecting fatigue damage. The fatigue experiments and magnetic memory testing were conducted on various types of weld. The experiment results reveal the limitations of using the original metal magnetic memory signal in the identification of the weld fatigue damage stage. To more accurately characterize the fatigue damage stage, multiple types of information entropies of metal magnetic memory signals are extracted, and the identification method based on fused information entropy is proposed. The results demonstrate that the change features of multiple types of information entropy can more accurately characterize the fatigue damage stage of weld compared with original metal magnetic memory signal. Moreover, the proposed fused information entropy contains the primary information of various entropies, resolving discrepancies in different entropy results for the same specimen, and enhances the accuracy of identification.

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References

  1. Z.F. He, H. Zhang, H. Ma et al., Study on Magnetic Memory Detection of Weld Fatigue Damage by using the Relative Entropy Theory, J. Magn. Magn. Mater., 2023, 570, 170472.

    Article  CAS  Google Scholar 

  2. S.K. Ren and R.L. Zu, Fatigue test on Defective Welded joints based on Magnetic Memory Technology, Acta Aeronaut. Astronaut. Sin., 2019, 40(03), p 251–262.

    Google Scholar 

  3. K. Tong, H. Zhang, R. Zhao, J. Zhou, and H. Ying, Investigation of SMFL Monitoring Technique for Evaluating the Load-Bearing Capacity of RC Bridges, Eng. Struct., 2023, 15(293), p 116667.

    Article  Google Scholar 

  4. Y. Wu, Fracture and fatigue, China University of Geosciences Press. Springer, Cham, 2009.

    Google Scholar 

  5. L.H. Su, X.H. Ma, G. Chen et al., Experimental Study on Magnetic Memory Detection method for Fatigue Damage of Ferromagnetic Components, J. Test. Meas. Technol., 2009, 23(02), p 145–150.

    Google Scholar 

  6. Z. Hu, J. Fan, S. Wu, H. Dai, and S. Liu, Characteristics of Metal Magnetic Memory Testing of 35CrMo Steel during Fatigue Loading, Metals., 2018, 8(2), p 119.

    Article  Google Scholar 

  7. J.C. Leng, M.Q. Xu, K. Wang et al., Fatigue Damage Monitoring based on Magnetic Memory Technology, J. Mater. Eng., 2011, 5, p 26–29.

    Google Scholar 

  8. J.C. Leng, H. Zhang, G.Q. Zhou et al., Experimental Study on Magnetic Memory Testing for Fatigue Life Assessment of Remanufactured Sucker Rods, J. Mater. Eng., 2016, 44(9), p 103–108.

    Google Scholar 

  9. B. Liu, Z. Zeng, and H. Wang, Study on the Early Fatigue Damage Evaluation of high Strength Steel by using three Components of Metal Magnetic Memory Signal, NDT E Int., 2021, 117, 102380.

    Article  CAS  Google Scholar 

  10. Z.C. Qian, H.H. Huang, S.L. Jiang et al., Research on the Magnetic Memory Signal of Ferromagnetic Material Tension/Compression Fatigue, J. Electron. Meas. Instrum., 2016, 30(4), p 506–517.

    Google Scholar 

  11. X.J. Di, W.S. Li, B.Y. Huang et al., Study on the Magnetic Memory Characteristics of Welded Cracked Metals based on Differential Methods, Weld. Tech., 2006, 35(4), p 14–15.

    Google Scholar 

  12. X.J. Di, W.S. Li, S.W. Bai et al., Quantitative Evaluation of Metal Magnetic Memory of Weld Cracks, Mate. Eng., 2006, 7, p 56–60.

    Google Scholar 

  13. X. Zhao, S. Su, W. Wang et al., Metal Magnetic Memory Inspection of Q345B Steel Beam in Four point Bending Fatigue Test, J. Magn. Magn. Mater., 2020, 514, 167155.

    Article  CAS  Google Scholar 

  14. W. Wang, H. Fan, S.Q. Su et al., Experimental Study on Magnetic Memory Detection of Hidden Damage in Butt Welds of Steel Structures, J. **’an Univ. Arc. Technol., 2014, 46(04), p 497–501.

    Google Scholar 

  15. Y. Yang, X. Ma, S. Su, and W. Wang, Theoretical and Experimental Analysis of the Correlation between Magnetic Memory Signals and Cumulative Ductile Damage of Butt Weld under Low Cycle Fatigue, J. Magn. Magn. Mater., 2023, 15(580), p 170911.

    Article  Google Scholar 

  16. K. Xu, K. Yang, J. Liu et al., Investigation of Magnetic Memory Signal of Propagation of Buried Crack under Applied Load, Res. Nondestruct. Eval., 2021, 32(1), p 1–9.

    Article  Google Scholar 

  17. H.Y. **ng, H. Ge, Y.T. Han et al., Quantitative Evaluation of Weld Grade Magnetic Memory based on Entropy Strip and DS Theory, Chin. J. Sci. Instrum., 2016, 37(03), p 610–616.

    Google Scholar 

  18. J.L. Ren, X. Chen, S.C. Luo et al., Research on Two-Dimensional Magnetic Memory Detection of High-Cycle Fatigue Damage, Acta Aeronaut. Sin., 2012, 33(6), p 1147–1155.

    CAS  Google Scholar 

  19. W.M. Zhang, D.C. Qiu, X. Yu et al., Discussion on Stress Quantitative Evaluation using Metal Magnetic Memory Method, J. Mecha. Eng., 2015, 51(8), p 21–24.

    CAS  Google Scholar 

  20. H.G. Liu, W.M. Zhang, X.Y. Mao et al., Multi-Parameter Identification System of Weld Defects based on Magnetic Memory Testing, Manufa. Auto., 2009, 31(2), p 811–814.

    CAS  Google Scholar 

  21. W.R. Shi, Y.S. Jiang, and Y. Zhao, A Backbone Formulation Algorithm in Wireless Sensor Network based on Cross-Entropy Method, Instrumentation, 2014, 1(1), p 38–48.

    Google Scholar 

  22. T. Liu and C.Y. Liang, Fault Diagnosis of Screw Compressor based on PSO-SVC with Information Entropy Fusion, J. Vib. Measur. Diagn., 2022, 42(01), p 147.

    CAS  Google Scholar 

  23. W. Deng, R. Yao, H. Zhao et al., A Novel Intelligent Diagnosis method using Optimal LS-SVM with Improved PSO Algorithm, Soft. Comput., 2019, 23(7), p 2445.

    Article  Google Scholar 

  24. D.L. Atherton and D.C. Jiles, Effects of Stress on Magnetization, NDT E Int., 1986, 19(1), p 15–19.

    Article  Google Scholar 

  25. S. Bao, W.L. **, M.F. Huang et al., Piezomagnetic Hysteresis as a Non-destructive Measure of the Metal Fatigue Process, NDT E Int., 2010, 43(8), p 706–712.

    Article  CAS  Google Scholar 

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Acknowledgment

This study was supported by the National Natural Science Foundation of China (U20A20314, 52278146, 52278291, 52308301), the Natural Science Fund for Distinguished Young Scholars of Chongqing (cstc2020jcyj-jqX0006), the Chongqing Natural Science Foundation of China (cstc2019jcyj-cxttX0004, cstc2020yszx-jscxX0003), the Research and Innovation Program for Graduate Students in Chongqing (CYB240247) and the Science and Technology Project of Guizhou Provincial Transportation Department (2020-123-017).

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Authors and Affiliations

  1. State Key Laboratory of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing, 400074, China

    Zhenfeng He, Hong Zhang, Senhua Zhang, Yang Zou, Kai Tong & Jianting Zhou

  2. School of Materials Science and Engineering, Chongqing Jiaotong University, Chongqing, 400074, China

    Leng Liao

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  1. Zhenfeng He
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  2. Hong Zhang
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  3. Senhua Zhang
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  4. Yang Zou
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  5. Kai Tong
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  6. Jianting Zhou
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  7. Leng Liao
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Correspondence to Leng Liao.

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He, Z., Zhang, H., Zhang, S. et al. Study on the Judgment of Fatigue Damage Stages in Welds Based on Entropy Analysis. J. of Materi Eng and Perform (2024). https://doi.org/10.1007/s11665-024-09794-9

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  • DOI: https://doi.org/10.1007/s11665-024-09794-9

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