Smart Structures and Systems

  • 제26권2호
  • /
  • Pages.227-239
  • /
  • 2020
  • /
  • 1738-1584(pISSN)
  • /
  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Structural health monitoring of high-speed railway tracks using diffuse ultrasonic wave-based condition contrast: theory and validation

  • Wang, Kai (Interdisciplinary Division of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University) ;
  • Cao, Wuxiong (Department of Mechanical Engineering, The Hong Kong Polytechnic University) ;
  • Su, Zhongqing (Department of Mechanical Engineering, The Hong Kong Polytechnic University) ;
  • Wang, Pengxiang (Southwest Jiaotong University Railway Development Co., Ltd.) ;
  • Zhang, Xiongjie (Southwest Jiaotong University Railway Development Co., Ltd.) ;
  • Chen, Lijun (Southwest Jiaotong University Railway Development Co., Ltd.) ;
  • Guan, Ruiqi (Department of Civil Engineering, Monash University) ;
  • Lu, Ye (Department of Civil Engineering, Monash University)
  • 투고 : 2019.12.05
  • 심사 : 2020.03.28
  • 발행 : 2020.08.25
⟨ 이전 논문 다음 논문 ⟩

초록

Despite proven effectiveness and accuracy in laboratories, the existing damage assessment based on guided ultrasonic waves (GUWs) or acoustic emission (AE) confronts challenges when extended to real-world structural health monitoring (SHM) for railway tracks. Central to the concerns are the extremely complex signal appearance due to highly dispersive and multimodal wave features, restriction on transducer installations, and severe contaminations of ambient noise. It remains a critical yet unsolved problem along with recent attempts to implement SHM in bourgeoning high-speed railway (HSR). By leveraging authors' continued endeavours, an SHM framework, based on actively generated diffuse ultrasonic waves (DUWs) and a benchmark-free condition contrast algorithm, has been developed and deployed via an all-in-one SHM system. Miniaturized lead zirconate titanate (PZT) wafers are utilized to generate and acquire DUWs in long-range railway tracks. Fatigue cracks in the tracks show unique contact behaviours under different conditions of external loads and further disturb DUW propagation. By contrast DUW propagation traits, fatigue cracks in railway tracks can be characterised quantitatively and the holistic health status of the tracks can be evaluated in a real-time manner. Compared with GUW- or AE-based methods, the DUW-driven inspection philosophy exhibits immunity to ambient noise and measurement uncertainty, less dependence on baseline signals, use of significantly reduced number of transducers, and high robustness in atrocious engineering conditions. Conformance tests are performed on HSR tracks, in which the evolution of fatigue damage is monitored continuously and quantitatively, demonstrating effectiveness, adaptability, reliability and robustness of DUW-driven SHM towards HSR applications.

키워드

과제정보

The work was supported by a General Project (No. 51875492) and a Key Project (No. 51635008) received from the National Natural Science Foundation of China. The authors acknowledge the support from the Hong Kong Research Grants Council via General Research Funds (Nos.: 15201416 and 15212417). Z. Su thanks the National Rail Transit Electrification and Automation Engineering Technology Research Center for a research grant (No. BBY8).

참고문헌

  1. Adams, D.E. (2007), Health Monitoring of Structural Materials and Components: Methods with Applications, Hoboken: John Wiley & Sons, Ltd.
  2. Adler, P.H., Olson, G.B. and Owen, W.S. (1986), "Strain hardening of Hadfield manganese steel", Metallurg. Mater. Transact. A, 17, 1725-1737. https://doi.org/10.1007/BF02817271
  3. Anugonda, P., Wiehn, J.S. and Turner, J.A. (2001), "Diffusion of ultrasound in concrete", Ultrasonics, 39, 429-435. https://doi.org/10.1016/S0041-624X(01)00077-4
  4. Bao, P., Yuan, M., Dong, S., Song, H. and Xue, J. (2013), "Fiber Bragg grating sensor fatigue crack real-time monitoring based on spectrum cross-correlation analysis", J. Sound Vib., 332, 43-57. https://doi.org/10.1016/j.jsv.2012.07.049
  5. Bartoli, I., di Scalea, F.L., Fateh, M. and Viola, E. (2005), "Modeling guided wave propagation with application to the long-range defect detection in railroad tracks", Ndt E Int., 38, 325-334. https://doi.org/10.1016/j.ndteint.2004.10.008
  6. BBC News, Ed. (2016), "India Train Crash: 115 Killed in Derailment near Kanpur."
  7. Buck, O., Thompson, R.B. and Rehbein, D.K. (1988), "Ultrasonic measurements of crack tip shielding by closure", Mater. Sci. Eng.: A, 103, 37-42. https://doi.org/10.1016/0025-5416(88)90549-6
  8. Cawley, P., Lowe, M.J.S., Alleyne, D.N., Pavlakovic, B. and Wilcox, P. (2003), "Practical long range guided wave inspection - Applications to pipes and rail", Mater. Eval., 61, 66-74.
  9. Chen, X., Michaels, J.E., Lee, S.J. and Michaels, T.E. (2012), "Load-differential imaging for detection and localization of fatigue cracks using Lamb waves", Ndt E Int., 51, 142-149. https://doi.org/10.1016/j.ndteint.2012.05.006
  10. Clark, R. (2004), "Rail flaw detection: overview and needs for future developments", Ndt E Int., 37, 111-118. https://doi.org/10.1016/j.ndteint.2003.06.002
  11. Croxford, A.J., Cheng, J. and Potter, J.N. (2016), "Nonlinear phased array imaging", Proceedings of Health Monitoring of Structural and Biological Systems 2016, 98052B, Las Vegas, NV, USA, April. https://doi.org/10.1117/12.2224744
  12. Gandhi, N., Michaels, J.E. and Lee, S.J. (2012), "Acoustoelastic Lamb wave propagation in biaxially stressed plates", J. Acoust. Soc. Am., 132, 1284-1293. https://doi.org/10.1121/1.4740491
  13. Ghiasi, R. and Ghasemi, M.R. (2018), "Optimization-based method for structural damage detection with consideration of uncertainties-a comparative study", Smart Struct. Syst., Int. J., 22(5), 561-574. https://doi.org/10.12989/sss.2018.22.5.561
  14. Han, H., Lu, G., Cong, P., Zhang, Q. and Wu, G. (2014), "Development of novel rail non-destructive inspection technologies", Sensors Transduc., 179, 121.
  15. He, W.Y., Zhu, S. and Ren, W.X. (2018), "Progressive damage detection of thin plate structures using wavelet finite element model updating", Smart Struct. Syst., Int. J., 22(3), 277-290. https://doi.org/10.12989/sss.2018.22.3.277
  16. Hilloulin, B., Zhang, Y., Abraham, O., Loukili, A., Grondin, F., Durand, O. and Tournat, V. (2014), "Small crack detection in cementitious materials using nonlinear coda wave modulation", Ndt E Int., 68, 98-104. https://doi.org/10.1016/j.ndteint.2014.08.010
  17. Hong, M., Wang, Q., Su, Z. and Cheng, L. (2014), "In situ health monitoring for bogie systems of CRH380 train on Beijing-Shanghai high-speed railway", Mech. Syst. Signal Process, 45, 378-395. https://doi.org/10.1016/j.ymssp.2013.11.017
  18. Lanza di Scalea, F., Rizzo, P., Coccia, S., Bartoli, I., Fateh, M., Viola, E. and Pascale, G. (2005), "Non-contact ultrasonic inspection of rails and signal processing for automatic defect detection and classification", Insight-Non-Destruct. Test. Condit. Monitor., 47, 346-353. https://doi.org/10.1784/insi.47.6.346.66449
  19. Larose, E., Planes, T., Rossetto, V. and Margerin, L. (2010), "Locating a small change in a multiple scattering environment", Appl. Phys. Lett., 96, 204101. https://doi.org/10.1063/1.3431269
  20. Li, F., Meng, G., Kageyama, K., Su, Z. and Ye, L. (2009), "Optimal mother wavelet selection for lamb wave analyses", J. Intel. Mater. Syst. Struct., 20, 1147-1161. https://doi.org/10.1177/1045389X09102562
  21. Liu, Z., Li, W., Xue, F., Xiafang, J., Bu, B. and Yi, Z. (2015), "Electromagnetic tomography rail defect inspection", IEEE Trans. Magn., 51, 1-7. https://doi.org/10.1109/TMAG.2015.2430283
  22. Lobkis, O.I. and Weaver, R.L. (2003), "Coda-wave interferometry in finite solids: Recovery of P-to-S conversion rates in an elastodynamic billiard", Phys. Rev. Lett., 90, 254302. https://doi.org/10.1103/PhysRevLett.90.254302
  23. Mair, C. and Fararooy, S. (1998), "Practice and potential of computer vision for railways", In: IEE Seminar Condition Monitoring for Rail Transport Systems, London, UK, November. https://doi.org/10.1049/ic:19980983
  24. Mariani, S., Nguyen, T., Zhu, X. and Lanza di Scalea, F. (2017), "Field test performance of noncontact ultrasonic rail inspection system", J. Transport. Eng., Part A: Syst., 143, 04017007. https://doi.org/10.1061/JTEPBS.0000026
  25. Michaels, J.E. and Michaels, T.E. (2005), "Detection of structural damage from the local temporal coherence of diffuse ultrasonic signals", IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 52, 1769-1782. https://doi.org/10.1109/TUFFC.2005.1561631
  26. Ohara, Y., Mihara, T., Sasaki, R., Ogata, T., Yamamoto, S., Kishimoto, Y. and Yamanaka, K. (2007), "Imaging of closed cracks using nonlinear response of elastic waves at subharmonic frequency", Appl. Phys. Lett., 90, 011902. https://doi.org/10.1063/1.2426891
  27. Ohara, Y., Horinouchi, S., Hashimoto, M., Shintaku, Y. and Yamanaka, K. (2011), "Nonlinear ultrasonic imaging method for closed cracks using subtraction of responses at different external loads", Ultrasonics, 51, 661-666. https://doi.org/10.1016/j.ultras.2010.12.010
  28. Ph Papaelias, M., Roberts, C. and Davis, C.L. (2008), "A review on non-destructive evaluation of rails: State-of-the-art and future development", Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 222, 367-384. https://doi.org/10.1243/09544097JRRT209
  29. Pippan, R. and Hohenwarter, A. (2017), "Fatigue crack closure: a review of the physical phenomena", Fatigue Fract. Eng. Mater. Struct., 40, 471-495. https://doi.org/10.1111/ffe.12578
  30. Planes, T. and Larose, E. (2013), "A review of ultrasonic Coda Wave Interferometry in concrete", Cement Concrete Res., 53, 248-255. https://doi.org/10.1016/j.cemconres.2013.07.009
  31. Rajamaki, J., Vippola, M., Nurmikolu, A. and Viitala, T. (2018), "Limitations of eddy current inspection in railway rail evaluation", Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 232, 121-129. https://doi.org/10.1016/j.cemconres.2013.07.009
  32. Rao, J., Ratassepp, M. and Fan, Z. (2016), "Guided wave tomography based on full waveform inversion", IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 63, 737-745. https://doi.org/10.1109/TUFFC.2016.2536144
  33. Santa-Aho, S., Sorsa, A., Nurmikolu, A. and Vippola, M. (2014), "Review of railway track applications of Barkhausen noise and other magnetic testing methods", Insight - Non-Destruct. Test. Condit. Monitor., 56, 657-663. https://doi.org/10.1784/insi.2014.56.12.657
  34. Shen, Y. and Cesnik, C.E. (2018), "Local interaction simulation approach for efficient modeling of linear and nonlinear ultrasonic guided wave active sensing of complex structures", J. Nondest. Eval., 1(1). https://doi.org/10.1115/1.4037545
  35. Song, Z., Yamada, T., Shitara, H. and Takemura, Y. (2011), "Detection of damage and crack in railhead by using eddy current testing", J. Electromagn. Anal. Applicat., 3, 546. https://doi.org/10.4236/jemaa.2011.312082
  36. Su, Z., Zhou, C., Hong, M., Cheng, L., Wang, Q. and Qing, X. (2014), "Acousto-ultrasonics-based fatigue damage characterization: Linear versus nonlinear signal features", Mech. Syst. Signal Process, 45, 225-239. https://doi.org/10.1016/j.ymssp.2013.10.017
  37. Thakkar, N.A., Steel, J.A., Reuben, R.L., Knabe, G., Dixon, D. and Shanks, R.L. (2006), "Monitoring of rail-wheel interaction using acoustic emission (AE)", Adv. Mater. Res., 13, 161-168. https://doi.org/10.4028/www.scientific.net/AMR.13-14.161
  38. Wang, Q., Yuan, S., Hong, M. and Su, Z. (2015), "On time reversal-based signal enhancement for active lamb wave-based damage identification", Smart Struct. Syst., Int. J., 15(6), 1463-1479. https://doi.org/10.12989/sss.2015.15.6.1463
  39. Wang, J., Liu, X.Z. and Ni, Y.Q. (2018), "A Bayesian probabilistic approach for acoustic emission‐based rail condition assessment", Comput.‐Aided Civil Inform., 33, 21-34. https://doi.org/10.1111/mice.12316
  40. Wang, K., Li, Y., Su, Z., Guan, R., Lu, Y. and Yuan, S. (2019a), "Nonlinear aspects of "breathing" crack-disturbed plate waves: 3-D analytical modeling with experimental validation", Int. J. Mech. Sci., 159, 140-150. https://doi.org/10.1016/j.ijmecsci.2019.05.036
  41. Wang, N.B., Ren, W.X. and Huang, T.L. (2019b), "Baseline-free damage detection method for beam structures based on an actual influence line", Smart Struct. Syst., Int. J., 24(4), 475-490. https://doi.org/10.12989/sss.2019.24.4.475
  42. Zhang, X., Feng, N., Wang, Y. and Shen, Y. (2015), "Acoustic emission detection of rail defect based on wavelet transform and Shannon entropy", J. Sound Vib., 339, 419-432. https://doi.org/10.1016/j.jsv.2014.11.021
  43. Zhang, Y., Tournat, V., Abraham, O., Durand, O., Letourneur, S., Le Duff, A. and Lascoup, B. (2017), "Nonlinear coda wave interferometry for the global evaluation of damage levels in complex solids", Ultrasonics, 73, 245-252. https://doi.org/10.1016/j.ultras.2016.09.015
  44. Zhang, X., Hao, Q., Wang, K., Wang, Y., Shen, Y. and Hu, H. (2018a), "An investigation on acoustic emission detection of rail crack in actual application by chaos theory with improved feature detection method", J. Sound Vib., 436, 165-182. https://doi.org/10.1016/j.jsv.2018.09.014
  45. Zhang, Y., Larose, E., Moreau, L. and d'Ozouville, G. (2018b), "Three-dimensional in-situ imaging of cracks in concrete using diffuse ultrasound", Struct. Health Monit., 17, 279-284. https://doi.org/10.1177/1475921717690938
  46. Zuo, P., Zhou, Y. and Fan, Z. (2016), "Numerical studies of nonlinear ultrasonic guided waves in uniform waveguides with arbitrary cross sections", AIP Advances, 6, 075207. https://doi.org/10.1063/1.4959005