Structural Monitoring and Maintenance

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

A review of recent research advances on structural health monitoring in Western Australia

  • Li, Jun (Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University) ;
  • Hao, Hong (Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University)
  • Received : 2015.12.31
  • Accepted : 2016.03.03
  • Published : 2016.03.25
⟨ Previous Next ⟩

Abstract

Structural Health Monitoring (SHM) has been attracting numerous research efforts around the world because it targets at monitoring structural conditions and performance to prevent catastrophic failure, and to provide quantitative data for engineers and infrastructure owners to design a reliable and economical asset management strategy. In the past decade, with supports from Australian Research Council (ARC), Cooperative Research Center for Infrastructure and Engineering Asset Management (CIEAM), CSIRO and industry partners, intensive research works have been conducted in the School of Civil, Environmental and Mining Engineering, University of Western Australia and Centre for Infrastructural Monitoring and Protection, Curtin University on various techniques of SHM. The researches include the development of hardware, software and various algorithms, such as various signal processing techniques for operational modal analysis, modal analysis toolbox, non-model based methods for assessing the shear connection in composite bridges and identifying the free spanning and supports conditions of pipelines, vibration based structural damage identification and model updating approaches considering uncertainty and noise effects, structural identification under moving loads, guided wave propagation technique for detecting debonding damage, and relative displacement sensors for SHM in composite and steel truss bridges. This paper aims at summarizing and reviewing the recent research advances on SHM of civil infrastructure in Western Australia.

Keywords

References

  1. Aktan A.E., Catbas F.N., Grimmelsman K.A. and Tsikos, C.J. (2000), "Issues in infrastructure health monitoring for management", J. Eng. Mech.-ASCE, 126(7), 711-724. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:7(711)
  2. Alamdari, M.M., Samali, B. and Li, J. (2015), "Damage localization based on symbolic time series analysis", Struct. Control Health Monit., 22(2), 374-393. https://doi.org/10.1002/stc.1683
  3. Amirebrahimi, S., Rajabifard, A., Mendis, P. and Ngo, T. (2015), "A framework for a microscale flood damage assessment and visualization for a building using BIM-GIS integration", Int. J. Digital Earth, DOI:10.1080/17538947.2015.1034201.
  4. Ay, A.M. and Wang, Y. (2014), "Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion", Struct. Health Monit., 13(4), 445-460. https://doi.org/10.1177/1475921714542891
  5. Bakhary, N., Hao, H. and Deeks, A.J. (2007), "Damage detection using artificial neural network with consideration of uncertainties", Eng. Struct., 29(11), 2806-2815. https://doi.org/10.1016/j.engstruct.2007.01.013
  6. Bakhary, N., Hao, H. and Deeks, A. (2010a), "Structure damage detection using neural network with multi-stage substructuring", Adv. Struct. Eng., 13(1), 95-110. https://doi.org/10.1260/1369-4332.13.1.95
  7. Bakhary, N., Hao, H. and Deeks, A. (2010b), "Substructuring technique for damage detection using statistical multi-stage artificial neural network", Adv. Struct. Eng., 13(4), 619-640. https://doi.org/10.1260/1369-4332.13.4.619
  8. Ban, H., Uy, B., Pathirana, S.W., Henderson, I., Mirza, O. and Zhu, X. (2015), "Time-dependent behaviour of composite beams with blind bolts under sustained loads", J. Constr. Steel Res., 112, 196-207. https://doi.org/10.1016/j.jcsr.2015.05.004
  9. Bao, C., Hao, H., Li, Z.X. and Zhu, X. (2009), "Time-varying system identification using a newly improved HHT algorithm", Computers & Structures, 87(23), 1611-1623. https://doi.org/10.1016/j.compstruc.2009.08.016
  10. Bao, C., Hao, H. and Li, Z.X. (2013a), "A study of variability and applicability of various signal processing techniques in structural system identification", Australian J. Struct. Eng., 14(1), 97-114.
  11. Bao, C., Hao, H. and Li, Z.X. (2013b), "Multi-stage identification scheme for detecting damage in structures under ambient excitations", Smart Mater. Struct., 22(4), 045006. https://doi.org/10.1088/0964-1726/22/4/045006
  12. Bao, C., Hao, H. and Li, Z.X. (2013c), "Integrated ARMA model method for damage detection of subsea pipeline system", Eng. Struct., 48, 176-192. https://doi.org/10.1016/j.engstruct.2012.09.033
  13. Bao, C., Hao, H. and Li, Z.X. (2013d), "Vibration-based structural health monitoring of offshore pipelines: numerical and experimental study", Struct. Control Health Monit., 20(5), 769-788. https://doi.org/10.1002/stc.1494
  14. Bastidas-Arteaga, E., Schoefs, F., Stewart, M.G. and Wang, X. (2013), "Influence of global warming on durability of corroding RC structures: A probabilistic approach", Eng. Struct., 51, 259-266. https://doi.org/10.1016/j.engstruct.2013.01.006
  15. Bastidas-Arteaga, E. and Stewart, M.G. (2015), "Damage risks and economic assessment of climate adaptation strategies for design of new concrete structures subject to chloride-induced corrosion", Struct. Saf., 52, 40-53. https://doi.org/10.1016/j.strusafe.2014.10.005
  16. Brownjohn, J.M.W. (2007). "Structural health monitoring of civil infrastructure", Philos. T. R. Soc. A, 365(1851), 589-622. https://doi.org/10.1098/rsta.2006.1925
  17. Brownjohn, J.M.W., Dumanoglu, A.A. and Severn, R.T. (1992), "Ambient vibration survey of the fatih sultan mehmet (second Bosporus) suspension bridge", Earthq. Eng. Struct. D., 21(10), 907-924. https://doi.org/10.1002/eqe.4290211005
  18. Caprani, C.C., OBrien, E.J. and McLachlan, G.J. (2008), "Characteristic traffic load effects from a mixture of loading events on short to medium span bridges", Struct. Saf., 30(5), 394-404. https://doi.org/10.1016/j.strusafe.2006.11.006
  19. Carden, E.P. and Fanning, P. (2004), "Vibration based condition monitoring: a review", Struct. Health Monit., 3(4), 355-377. https://doi.org/10.1177/1475921704047500
  20. Chan T. and Thambiratnam D.P. (2011), Structural Health Monitoring in Australia, New York: Nova Science Publisher.
  21. Dackermann, U., Skinner, B. and Li, J. (2014), "Guided wave-based condition assessment of in situ timber utility poles using machine learning algorithms", Struct. Health Monit., 13(4), 374-388. https://doi.org/10.1177/1475921714521269
  22. De Roeck, G., Peeters, B. and Ren, W.X. (2000), "Benchmark study on system identification through ambient vibration measurements", Proceedings of the IMAC-XVIII: The 18th International Modal Analysis Conference, San Antonio, TX.
  23. Ding, L., Hao, H. and Zhu, X. (2009), "Evaluation of dynamic vehicle axle loads on bridges with different surface conditions", J. Sound Vib., 323(3), 826-848. https://doi.org/10.1016/j.jsv.2009.01.051
  24. Ding, L., Hao, H., Xia, Y. and Deeks, A. (2012), "Evaluation of bridge load carrying capacity using updated finite element model and nonlinear analysis", Adv. Struct. Eng., 15(10), 1739-1750. https://doi.org/10.1260/1369-4332.15.10.1739
  25. Doebling, S.W., Farrar, C.R. and Cornwell, P.J. (1997), "DIAMOND: a graphical interface toolbox for comparative modal analysis and damage identification", Proceedings of the 6th International Conference on Recent Advances in Structural Dynamics, Southampton.
  26. Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Digest, 30(2), 91-105. https://doi.org/10.1177/058310249803000201
  27. Duan, Z., Yan, G., Ou, J. and Spencer, B.F. (2007), "Damage detection in ambient vibration using proportional flexibility matrix with incomplete measured DOFs", Struct. Control Health Monit., 14(2), 186-196. https://doi.org/10.1002/stc.149
  28. Fan, W. and Qiao, P. (2011), "Vibration-based damage identification methods: a review and comparative study", Struct. Health Monit., 10(1), 83-111. https://doi.org/10.1177/1475921710365419
  29. Farrar C.R. and Worden K. (2007), "An introduction to structural health monitoring", Philos. T. R. Soc. A, 365(1851), 303-315. https://doi.org/10.1098/rsta.2006.1928
  30. Farrar, C.R. and Lieven, N.A. (2007), "Damage prognosis: the future of structural health monitoring", Philos. T. R. Soc. A, 365(1851), 623-632. https://doi.org/10.1098/rsta.2006.1927
  31. Frangopol, D.M., Strauss, A. and Kim, S. (2008), "Use of monitoring extreme data for the performance prediction of structures: general approach", Eng. Struct., 30(12), 3644-3653. https://doi.org/10.1016/j.engstruct.2008.06.010
  32. Fujino, Y. (2002), "Vibration, control and monitoring of long-span bridges-recent research, developments and practice in Japan", J. Constr. Steel Res., 58(1), 71-91. https://doi.org/10.1016/S0143-974X(01)00049-9
  33. Hao, H. and Xia, Y. (2002), "Vibration-based damage detection of structures by genetic algorithm", J. Comput. Civil Eng.-ASCE, 16(3), 222-229. https://doi.org/10.1061/(ASCE)0887-3801(2002)16:3(222)
  34. Henderson, I.E.J., Zhu, X.Q., Uy, B. and Mirza, O. (2015), "Dynamic behaviour of steel-concrete composite beams with different types of shear connectors. Part I: Experimental study", Eng. Struct., 103, 298-307. https://doi.org/10.1016/j.engstruct.2015.08.035
  35. Huynh, C.P., Mustapha, S., Runcie, P. and Porikli, F. (2015), "Multi-class support vector machines for paint condition assessment on the Sydney Harbour Bridge using hyperspectral imaging", Struct. Monit. Maint., 2(3), 181-197. https://doi.org/10.12989/smm.2015.2.3.181
  36. Ko, J.M. and Ni, Y.Q. (2005), "Technology developments in structural health monitoring of large-scale bridges", Eng. Struct., 27(12), 1715-1725. https://doi.org/10.1016/j.engstruct.2005.02.021
  37. Lee, J.J. and Yun, C.B. (2006). "Damage diagnosis of steel girder bridges using ambient vibration data", Eng. Struct., 28(6), 912-925. https://doi.org/10.1016/j.engstruct.2005.10.017
  38. Lee, J., Guan, H., Loo, Y.C. and Blumenstein, M. (2012), "Refinement of backward prediction method for reliable artificial intelligence-based bridge deterioration modelling", Adv. Struct. Eng., 15(5), 825-836. https://doi.org/10.1260/1369-4332.15.5.825
  39. Lee, J., Guan, H., Loo, Y.C. and Blumenstein, M. (2014), "Development of a long-term bridge element performance model using Elman neural networks", J. Infrastruct. Syst.-ASCE, 20(3), 04014013. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000197
  40. Li, H.N, Yi, T.H., Ren, L., Li, D.S. and Huo, L.S. (2014a), "Reviews on innovations and applications in structural health monitoring for infrastructures", Struct. Monit. Maint., 1(1), 1-45. https://doi.org/10.12989/SMM.2014.1.1.001
  41. Li, J., Law, S.S. and Hao, H. (2013), "Improved damage identification in bridge structures subject to moving loads: numerical and experimental studies", Int. J. Mech. Sci., 74, 99-111. https://doi.org/10.1016/j.ijmecsci.2013.05.002
  42. Li, J. and Hao, H. (2014), "Substructure damage identification based on wavelet-domain response reconstruction", Struct. Health Monit., 13(4), 389-405. https://doi.org/10.1177/1475921714532991
  43. Li, J., Hao, H., Xia, Y. and Zhu, H.P. (2014b), "Damage detection of shear connectors in bridge structures with transmissibility in frequency domain", Int. J. Struct. Stability Dynam., 14(2), 1350061. https://doi.org/10.1142/S0219455413500612
  44. Li, J., Hao, H. and Zhu, H.P. (2014c), "Dynamic assessment of shear connectors in composite bridges with ambient vibration measurements", Adv. Struct. Eng., 17(5), 617-638. https://doi.org/10.1260/1369-4332.17.5.617
  45. Li, J., Hao, H., Xia, Y. and Zhu, H.P. (2015a), "Damage assessment of shear connectors with vibration measurements and power spectral density transmissibility", Struct. Eng. Mech., 54(2), 257-289. https://doi.org/10.12989/sem.2015.54.2.257
  46. Li, J., Hao, H. and Lo, J.V. (2015b), "Structural damage identification with power spectral density transmissibility: Numerical and experimental studies", Smart Struct. Syst., 15(1), 15-40. https://doi.org/10.12989/sss.2015.15.1.015
  47. Li, J., Hao, H. and Fan, X. (2015c), "Structural damage identification with extracted impulse response functions and optimal sensor locations", Electronic J. Struct. Eng., 14(1), 123-132.
  48. Li, J., Hao, H. and Chen, Z. (2015d), "Damage identification and optimal sensor placement for structures under unknown traffic-induced vibrations", J. Aerospace Eng.-ASCE, B4015001.
  49. Li, J., Hao, H., Fan, K. and Brownjohn, J. (2015e), "Development and application of a relative displacement sensor for structural health monitoring of composite bridges", Struct. Control Health Monit., 22(4), 726-742. https://doi.org/10.1002/stc.1714
  50. Li, J. and Hao, H. (2015), "Damage detection of shear connectors under moving loads with relative displacement measurements", Mech. Syst. Signal Pr., 60, 124-150.
  51. Li, J. and Hao, H. (online), "Health monitoring of joint conditions in steel truss bridges with relative displacement sensors", Measurement: J. Int. Measurement Confederation. doi:10.1016/j.measurement.2015.12.009.
  52. Lumentut, M. and Howard, I.M. (2015), "Parametric design-based modal damped vibrational piezoelectric energy harvesters with arbitrary proof mass offset: numerical and analytical validations", Mech. Syst. Signal Pr., 68-69, 562-586.
  53. Lynch, J.P. (2007), "An overview of wireless structural health monitoring for civil structures", Philos. T. R. Soc. A, 365(1851), 345-372. https://doi.org/10.1098/rsta.2006.1932
  54. Mahini S.S. Eslami, A. and Ronagh, H.R. (2012), "Lateral performance and load carrying capacity of an unreinforced, CFRP-retrofitted historical masonry vault-a case study", Constr. Build. Mater., 28(1), 146-156. https://doi.org/10.1016/j.conbuildmat.2011.08.013
  55. Mahmood, S.M., Haritos, N., Gad, E. and Zhang, L. (2014), "A multi-reference-based mode selection approach for the implementation of NExT-ERA in modal-based damage detection", Struct. Control Health Monit., 21(8), 1137-1153. https://doi.org/10.1002/stc.1638
  56. Mufti A.A. (2002), "Structural health monitoring of innovative Canadian civil engineering structures", Struct. Health Monit., 1(1), 89-103. https://doi.org/10.1177/147592170200100106
  57. Mustapha, S., Lu, Y., Li, J. and Ye, L. (2014), "Damage detection in rebar-reinforced concrete beams based on time reversal of guided waves", Struct. Health Monit., 13(4), 347-358. https://doi.org/10.1177/1475921714521268
  58. Ng, C.T. (2011), Probabilistic Methods for Structural Safety Evaluation, Damage Detection and Reliability Analysis of Structures, VDM Verlag Dr. Muller GmbH & Co. KG.
  59. Ng, C.T. (2014), "On the selection of advanced signal processing techniques for guided wave damage identification using a statistical approach", Eng. Struct., 64, 50-60.
  60. Nguyen, T., Chan, T., Thambiratnam, D.P. and King, L. (2015), "Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring", Mech. Syst. Signal Pr., 64-65, 313-324. https://doi.org/10.1016/j.ymssp.2015.04.003
  61. Nie, Z., Hao, H. and Ma, H. (2012), "Using vibration phase space topology changes for structural damage detection", Struct. Health Monit., 11(5), 538-557. https://doi.org/10.1177/1475921712447590
  62. Nie, Z., Hao, H. and Ma, H. (2013), "Structural damage detection based on the reconstructed phase space for reinforced concrete slab: Experimental study", J. Sound Vib., 332(4), 1061-1078. https://doi.org/10.1016/j.jsv.2012.08.024
  63. Ou, J. and Li, H. (2010), "Structural health monitoring in mainland China: review and future trends", Struct. Health Monit., 9(3), 219-231. https://doi.org/10.1177/1475921710365269
  64. Peng, X.L. and Hao, H. (2012), "A numerical study of damage detection of underwater pipeline using vibration-based method", Int. J. Struct. Stability Dynam., 12(3), 1250021. https://doi.org/10.1142/S0219455412500216
  65. Peng, X.L., Hao, H. and Li, Z.X. (2012), "Application of wavelet packet transform in subsea pipeline bedding condition assessment", Eng. Struct., 39, 50-65. https://doi.org/10.1016/j.engstruct.2012.01.017
  66. Peng, X.L., Hao, H., Li, Z.X. and Fan, K.Q. (2013), "Experimental study on subsea pipeline bedding condition assessment using wavelet packet transform", Eng. Struct., 48, 81-97. https://doi.org/10.1016/j.engstruct.2012.09.001
  67. Pines D.J. and Aktan A.E. (2002), "Status of structural health monitoring of long-span bridges in the United States", Prog. Struct. Eng. Mater., 4(4), 372-380. https://doi.org/10.1002/pse.129
  68. Ren, W.X., Sun, Z.S., Xia, Y., Hao, H. and Deeks, A.J. (2008), "Damage identification of shear connectors with wavelet packet energy: laboratory test study", J. Struct. Eng.-ASCE, 134(5), 832-841. https://doi.org/10.1061/(ASCE)0733-9445(2008)134:5(832)
  69. Samali, B., Li, J., Choi, F.C. and Crews, K. (2010), "Application of the damage index method for plate-like structures to timber bridges", Struct. Control Health Monit., 17(8), 849-871. https://doi.org/10.1002/stc.347
  70. Sharma, S. and Mukherjee, A. (2015), "Ultrasonic guided waves for monitoring corrosion in submerged plates", Struct. Control Health Monit., 22(1), 19-35. https://doi.org/10.1002/stc.1657
  71. Teughels, A. and De Roeck, G. (2005), "Damage detection and parameter identification by finite element model updating", Arch. Comput. Method. E., 12(2), 123-164. https://doi.org/10.1007/BF03044517
  72. Wahalathantri, B.L., Thambiratnam, D.P., Chan, T. and Fawzia, S. (2015), "Vibration based baseline updating method to localize crack formation and propagation in reinforced concrete members", J. Sound Vib., 344, 258-276. https://doi.org/10.1016/j.jsv.2015.01.043
  73. Wang, Y., Zhu, X., Hao, H. and Ou, J. (2009), "Guided wave propagation and spectral element method for debonding damage assessment in RC structures", J. Sound Vib., 324(3), 751-772. https://doi.org/10.1016/j.jsv.2009.02.028
  74. Wang, Y., Zhu, X., Hao, H. and Ou, J. (2011), "Spectral element model updating for damage identification using clonal selection algorithm", Adv. Struct. Eng., 14(5), 837-856. https://doi.org/10.1260/1369-4332.14.5.837
  75. Wang, Y. and Hao, H. (2014), "Damage identification of steel beams using local and global methods", Adv. Struct. Eng., 15(5), 807-824.
  76. Wang, Y., Hao, H., Zhu, X. and Ou, J. (2012), "Spectral element modelling of wave propagation with boundary and structural discontinuity reflections", Adv. Struct. Eng., 15(5), 855-870. https://doi.org/10.1260/1369-4332.15.5.855
  77. Wang, Y., Khoo, S., Li, A.J. and Hao, H. (2013), "FEM calibrated ARMAX model updating method for time domain damage identification", Adv. Struct. Eng., 16(1), 51-60. https://doi.org/10.1260/1369-4332.16.1.51
  78. Wang, Y. and Hao, H. (2013), "Damage identification of slab-girder structures: experimental studies", J. Civil Struct. Health Monit., 3(2), 93-103. https://doi.org/10.1007/s13349-013-0037-4
  79. Wang, Y. and Hao, H. (2013), "Damage identification scheme based on compressive sensing", J. Comput. Civil Eng., 29(2), 04014037. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000324
  80. Wong, K.Y. (2004), "Instrumentation and health monitoring of cable-supported bridges", Struct. Control Health Monit., 11(2), 91-124. https://doi.org/10.1002/stc.33
  81. Xia, Y., Hao, H., Brownjohn, J.M.W. and Xia, P.Q. (2002), "Damage identification of structures with uncertain frequency and mode shape data", Earthq. Eng. Struct. D., 31(5), 1053-1066. https://doi.org/10.1002/eqe.137
  82. Xia, Y. and Hao, H. (2003), "Statistical damage identification of structures with frequency changes", J. Sound Vib., 263(4), 853-870. https://doi.org/10.1016/S0022-460X(02)01077-5
  83. Xia, Y., Hao, H., Zanardo, G. and Deeks, A. (2006), "Long term vibration monitoring of an RC slab: temperature and humidity effect", Eng. Struct., 28(3), 441-452. https://doi.org/10.1016/j.engstruct.2005.09.001
  84. Xia, Y., Hao, H. and Deeks, A.J. (2007), "Dynamic assessment of shear connectors in slab-girder bridges", Eng. Struct., 29(7), 1475-1486. https://doi.org/10.1016/j.engstruct.2006.09.014
  85. Xia, Y., Hao, H., Deeks, A.J. and Zhu, X. (2008), "Condition assessment of shear connectors in slab-girder bridges via vibration measurements", J. Bridge Eng., 13(1), 43-54. https://doi.org/10.1061/(ASCE)1084-0702(2008)13:1(43)
  86. Xiong, C., Lu, X., Hori, M., Guan, H. and Xu, Z. (2015), "Building seismic response and visualization using 3D urban polygonal modeling", Automat. Constr., 55, 25-34. https://doi.org/10.1016/j.autcon.2015.03.023
  87. Yan, Y.J., Cheng, L., Wu, Z.Y. and Yam, L.H. (2007), "Development in vibration-based structural damage detection technique", Mech. Syst. Signal Pr., 21(5), 2198-2211. https://doi.org/10.1016/j.ymssp.2006.10.002
  88. Zanardo, G., Hao, H., Xia, Y. and Deeks, A. (2006), "Stiffness assessment through modal analysis of an RC slab bridge before and after strengthening", J. Bridge Eng.-ASCE,11(5), 590-601. https://doi.org/10.1061/(ASCE)1084-0702(2006)11:5(590)
  89. Zhu, X.Q., Hao, H. and Peng, X.L. (2008), "Dynamic assessment of underwater pipeline systems using statistical model updating", Int. J. Struct. Stability Dynam., 8(2), 271-297. https://doi.org/10.1142/S021945540800265X
  90. Zhu, X., Hao, H., Uy, B., Xia, Y. and Mirza, O. (2012), "Dynamic assessment of shear connection conditions in slab-girder bridges by Kullback-Leibler distance", Adv. Struct. Eng., 15(5), 771-780. https://doi.org/10.1260/1369-4332.15.5.771
  91. Zhu, X.Q., Hao, H. and Fan, K.Q. (2013), "Detection of delamination between steel bars and concrete using embedded piezoelectric actuators/sensors", J. Civil Struct. Health Monit., 3(2), 105-115. https://doi.org/10.1007/s13349-013-0039-2
  92. Zhu, X.Q. and Law, S.S. (2015), "Structural Health Monitoring Based on Vehicle-Bridge Interaction: Accomplishments and Challenges", Adv. Struct. Eng., 18(12), 1999-2016. https://doi.org/10.1260/1369-4332.18.12.1999

Cited by

  1. Vibration-based structural health monitoring of the aircraft large component vol.251, 2017, https://doi.org/10.1088/1757-899X/251/1/012093
  2. Improving substructure identification accuracy of shear structures using virtual control system vol.27, pp.2, 2018, https://doi.org/10.1088/1361-665X/aaa46f
  3. A Whole-Range S–N Curve for Fatigue Assessment of Steel Orthotropic Bridge Decks 2018, https://doi.org/10.1142/S0219455418400102
  4. Identification of Minor Structural Damage Based on Electromechanical Impedance Sensitivity and Sparse Regularization vol.31, pp.5, 2018, https://doi.org/10.1061/(ASCE)AS.1943-5525.0000892
  5. Operational modal identification of structures based on improved empirical wavelet transform vol.26, pp.3, 2019, https://doi.org/10.1002/stc.2323
  6. Using multi-type sensor measurements for damage detection of shear connectors in composite bridges under moving loads vol.20, pp.5, 2016, https://doi.org/10.12989/cac.2017.20.5.521
  7. Shaking table test of pounding tuned mass damper (PTMD) on a frame structure under earthquake excitation vol.20, pp.5, 2016, https://doi.org/10.12989/cac.2017.20.5.545
  8. A systematic method from influence line identification to damage detection: Application to RC bridges vol.20, pp.5, 2017, https://doi.org/10.12989/cac.2017.20.5.563
  9. Structural health monitoring using piezoceramic transducers as strain gauges and acoustic emission sensors simultaneously vol.20, pp.5, 2016, https://doi.org/10.12989/cac.2017.20.5.595
  10. Structural damage identification using cloud model based fruit fly optimization algorithm vol.67, pp.3, 2016, https://doi.org/10.12989/sem.2018.67.3.245
  11. Structural damage identification based on autoencoder neural networks and deep learning vol.172, pp.None, 2016, https://doi.org/10.1016/j.engstruct.2018.05.109
  12. Statistical Estimation of Perspective Damage Index for Vibration-Based Structural Health Monitoring vol.1172, pp.None, 2019, https://doi.org/10.1088/1742-6596/1172/1/012036
  13. Monitoring system of high-rise buildings, determined from the nature of the curvature of the elastic line of vertical elements vol.4, pp.None, 2016, https://doi.org/10.22227/2305-5502.2019.4.3
  14. Image reconstruction and characterisation of defects in a carbon fibre/epoxy composite monitored with guided waves vol.28, pp.6, 2019, https://doi.org/10.1088/1361-665x/ab1359
  15. Bayesian Nonparametric Modeling of Structural Health Indicators under Severe Typhoons and Its Application to Modeling Modal Frequency vol.32, pp.4, 2016, https://doi.org/10.1061/(asce)as.1943-5525.0001023
  16. PZT transducer array enabled pipeline defect locating based on time-reversal method and matching pursuit de-noising vol.28, pp.7, 2016, https://doi.org/10.1088/1361-665x/ab1cc9
  17. A Novel Artificial Bee Colony Algorithm for Structural Damage Detection vol.2020, pp.None, 2016, https://doi.org/10.1155/2020/3743089
  18. Machine Learning‐Enabled Smart Sensor Systems vol.2, pp.9, 2020, https://doi.org/10.1002/aisy.202000063
  19. Non-probabilistic method to consider uncertainties in structural damage identification based on Hybrid Jaya and Tree Seeds Algorithm vol.220, pp.None, 2020, https://doi.org/10.1016/j.engstruct.2020.110925
  20. A two-stage Kalman filter for the identification of structural parameters with unknown loads vol.26, pp.6, 2020, https://doi.org/10.12989/sss.2020.26.6.693
  21. A new physical parameter identification method for shear frame structures under limited inputs and outputs vol.24, pp.4, 2016, https://doi.org/10.1177/1369433220963733
  22. Damage quantification of beam structures using deflection influence line changes and sparse regularization vol.24, pp.9, 2021, https://doi.org/10.1177/1369433221992482
  23. Impact of Groundwater Level Change on Natural Frequencies of RC Buildings vol.11, pp.7, 2021, https://doi.org/10.3390/buildings11070265
  24. Nonlinear structural damage detection using output‐only Volterra series model vol.28, pp.9, 2021, https://doi.org/10.1002/stc.2802
  25. A new acoustic emission damage localization method using synchrosqueezed wavelet transforms picker and time-order method vol.20, pp.6, 2016, https://doi.org/10.1177/1475921720977041