Lei Liu,∗ Jianting Zhou,∗ Ruiqiang Zhao,∗∗ Renming Liu,∗ and Leng Liao∗∗
[1] Editorial Department of China Journal of Highway and Trans-port, Review on China’s Bridge Engineering Research: 2021,China Journal of Highway and Transport, 34(2), 2021, 1–97.360 [2] S.Y. Yu, X.B. Wu, G.H. Chen, H.P. Dai, et al., Application ofwireless sensor network in bridge health monitoring, Journalof Software, 26(06), 2015, 1486–1498. [3] Q. Pan, C. Shao, D. Xiao, et al., Robotic ultrasonic measure-ment of residual stress in complex curved surface components,Applied Bionics and Biomechanics, 1, 2019, 2797896. [4] G.L. Liu and Z.P. Zhang, Experimental research on ultrasonicnondestructive testing of concrete compressive strength, Jour-nal of Sichuan University of Science & Technology (NaturalScience Edition), 24(03), 2011, 258–260. [5] W.H. Hu, G. Peng, S.C. Huang, et al., Research on dynamicdamage characteristics of concrete based on acoustic emis-sion technology, Journal of Yangtze River Scientific ResearchInstitute, 32(2), 2015, 123–127. [6] M.M. Zakirnichnaya, O.R. Abdulganieva, and D.A. Yudicheva,Estimation of the limit state criterion for steels C1020 andA 516-55 with V-notch under quasistatic loading using acous-tic emission control, Materials Science Forum, 945, 2019,4642. [7] Y. Chen and S.Q. Zhou, The current research status of residualstress X-ray measurement method, Nondestructive Testing,23(1), 2001, 19–22. [8] Q.Y. Xie and X.S. Zhou, Introduction to the progress of X-raydiffraction, Physics, 41(11), 2012, 727–735. [9] W.H. Hu, G. Peng, S.C. Huang, et al., New method for fatigueresearch of reinforced concrete based on piezomagnetic effect,Journal of Building Structures, 37(4), 2016, 133–142. [10] C. Hao, and H.S. Ding, The characteristics and adaptabilityof magnetic measurement method to detect residual stress,Physical Testing and Testing, 35(06), 2017, 25–29. [11] J. Shen, B. Lin, Y.G. Chi, and M. Liu, Research statusof residual stress physical method measurement technology,Materials Review, 26(S1), 2012, 120–125. [12] A.A. Doubov, A study of metal properties using the method ofmagnetic memory, Metal Science and Heat Treatment, 39(9),1997, 401–405. [13] Z.D. Wang, K. Yao, K. Shen, et al., Research progress and somediscussions on metal magnetic memory detection technology,Experimental Mechanics, 27(2), 2012, 129–139. [14] P.P. Shi, Quantitative Research on Micro-Magnetic Detectionof Stress and Defects in Ferromagnetic Materials, DoctoralDissertation of Xidian University, 2017. [15] D.C. Jiles, Theory of the magnetomechanical effect, Journalof Physics D: Applied Physics, 28(8), 1995, 1537–1546. [16] J.L. Ren, C. Chen, C.K. Liu, et al., Experimental research onmicrocosmic mechanism of stress-magnetic effect for magneticmemory testing, Journal of Aeronautical Materials, 28(05),2008, 41–44. [17] W. Wang, S.C. Yi, S.Q. Su, et al., Research status andkey issues of nondestructive testing of metal magnetic mem-ory, China Journal of Highway and Transport, 32(9), 2019,1–21. [18] W.M. Zhang, H.G. Liu, and H.T. Sun, Experimental studyon the magnetic memory effect of low- and medium-carbonsteel during static tension, Journal of Beijing Institute ofTechnology, 24(7), 2004, 571–574. [19] P.J. Guo, X.D. Chen, W.H. Guan, et al., Effect of tensilestress on the variation of magnetic field of low-alloy steel,Journal of Magnetism and Magnetic Materials, 323, 2011,2474–2477. [20] W. Wang, S.C. Yi, and S.Q. Su, Experimental investigationof stress and damage characterization of steel beam bucklingusing magnetic memory signals, The Structural Design of Talland Special Buildings, 25(11), 2016, 505–518. [21] H.X. Ma, J.T. Zhou, R.Q. Zhao, et al., Non-destructive testingof steel bar stress based on metal magnetic memory technology,Journal of Jiangsu University (Natural Science Edition), 39(3),2018, 349–354. [22] C.Y. Pang, J.T. Zhou, R.Q. Zhao, et al., Research on internalforce detection method of steel bar in elastic and yielding stagebased on metal magnetic memory, Materials, 12(7), 2019,1167. [23] J. Fei and S. Wang, Feedback linearization-based adaptive fuzzysliding mode control of mems; triaxial gyroscope, InternationalJournal of Robotics & Automation, 28(1), 2013, 72–80. [24] P. Jha and B.B. Biswal, A neural network approach for inversekinematic of a SCARA manipulator, International Journal ofRobotics and Automation, 3(1), 2014, 31–40.
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