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http://dx.doi.org/10.12989/sem.2020.75.4.415

Multi-strategy structural damage detection based on included angle of vectors and sparse regularization  

Liu, Huanlin (MOE Key Laboratory of Disaster Forecast and Control in Engineering, School of Mechanics and Construction Engineering, Jinan University)
Yu, Ling (MOE Key Laboratory of Disaster Forecast and Control in Engineering, School of Mechanics and Construction Engineering, Jinan University)
Luo, Ziwei (MOE Key Laboratory of Disaster Forecast and Control in Engineering, School of Mechanics and Construction Engineering, Jinan University)
Chen, Zexiang (MOE Key Laboratory of Disaster Forecast and Control in Engineering, School of Mechanics and Construction Engineering, Jinan University)
Publication Information
Structural Engineering and Mechanics / v.75, no.4, 2020 , pp. 415-424 More about this Journal
Abstract
Recently, many structural damage detection (SDD) methods have been proposed to monitor the safety of structures. As an important modal parameter, mode shape has been widely used in SDD, and the difference of vectors was adopted based on sensitivity analysis and mode shapes in the existing studies. However, amplitudes of mode shapes in different measured points are relative values. Therefore, the difference of mode shapes will be influenced by their amplitudes, and the SDD results may be inaccurate. Focus on this deficiency, a multi-strategy SDD method is proposed based on the included angle of vectors and sparse regularization in this study. Firstly, inspired by modal assurance criterion (MAC), a relationship between mode shapes and changes in damage coefficients is established based on the included angle of vectors. Then, frequencies are introduced for multi-strategy SDD by a weighted coefficient. Meanwhile, sparse regularization is applied to improve the ill-posedness of the SDD problem. As a result, a novel convex optimization problem is proposed for effective SDD. To evaluate the effectiveness of the proposed method, numerical simulations in a planar truss and experimental studies in a six-story aluminum alloy frame in laboratory are conducted. The identified results indicate that the proposed method can effectively reduce the influence of noises, and it has good ability in locating structural damages and quantifying damage degrees.
Keywords
structural damage detection (SDD); multi-strategy method; sparse regularization; included angle of vectors;
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1 Yan, W.J., Zhao, M.Y., Sun, Q. and Ren, W.X. (2019), "Transmissibility-based system identification for structural health monitoring: Fundamentals, approaches, and applications", Mech. Syst. Signal Pr., 117, 453-482. https://doi.org/10.1016/j.ymssp.2018.06.053.   DOI
2 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.   DOI
3 Zhang, C.D. and Xu, Y.L. (2016), "Comparative studies on damage identification with Tikhonov regularization and sparse regularization", Struct. Control Hlth. Monit., 23(3), 560-579. https://doi.org/10.1002/stc.1785.   DOI
4 Zhao, J. and DeWolf, J.T. (1999), "Sensitivity study for vibrational parameters used in damage detection", J. Struct. Eng., 125(4), 410-416. https://doi.org/10.1061/(ASCE)0733-9445(1999)125:4(410).   DOI
5 Zhou, X.Q., Xia, Y. and Weng, S. (2015), "$L_1$ regularization approach to structural damage detection using frequency data", Struct. Hlth. Monit., 14(6), 571-582. https://doi.org/10.1177/1475921715604386.   DOI
6 Zhou, Y.L. and Wahab, M.A. (2017), "Cosine based and extended transmissibility damage indicators for structural damage detection", Eng. Struct., 141, 175-183. https://doi.org/10.1016/j.engstruct.2017.03.030.   DOI
7 Beck, A. and Teboulle, M. (2009), "A fast iterative shrinkage-thresholding algorithm for linear inverse problems", SIAM J. Imaging Sci., 2(1), 183-202. https://doi.org/10.1137/080716542.   DOI
8 Alkayem, N.F., Cao, M., Zhang, Y., Bayat, M. and Su, Z. (2018), "Structural damage detection using finite element model updating with evolutionary algorithms: a survey", Neural Comput. Appl., 30(2), 389-411. https://doi.org/10.1007/s00521-017-3284-1.   DOI
9 Allemang, R.J. (2003), "The modal assurance criterion - Twenty years of use and abuse", Sound Vib., 37(8), 14-23.
10 Bagherahmadi, S.A. and Seyedpoor, S.M. (2018), "Structural damage detection using a damage probability index based on frequency response function and strain energy concept", Struct. Eng. Mech., 67(4), 327-336. https://doi.org/10.12989/sem.2018.67.4.327.   DOI
11 Cawley, P. and Adams, R.D. (1979), "The location of defects in structures from measurements of natural frequencies", J. Strain Anal. Eng. Des., 14(2), 49-57. https://doi.org/10.1243/03093247V142049.   DOI
12 Fan, W. and Qiao, P. (2011), "Vibration-based damage identification methods: A review and comparative study", Struct. Hlth. Monit., 10(1), 83-111. https://doi.org/10.1177/1475921710365419.   DOI
13 Cha, Y.J. and Buyukozturk, O. (2015), "Structural damage detection using modal strain energy and hybrid multiobjective optimization", Comput.-Aided Civ. Inf., 30(5), 347-358. https://doi.org/10.1111/mice.12122.   DOI
14 Chang, M., Kim, J.K. and Lee, J. (2019), "Hierarchical neural network for damage detection using modal parameters", Struct. Eng. Mech., 70(4), 457-466. https://doi.org/10.12989/sem.2019.70.4.457.   DOI
15 Esfandiari, A., Chaei, M.G. and Rofooei, F.R. (2018), "A structural model updating method using incomplete power spectral density function and modal data", Struct. Eng. Mech., 68(1), 39-51. https://doi.org/10.12989/sem.2018.68.1.039.   DOI
16 Koutsovasilis, P. and Beitelschmidt, M. (2007), "Model reduction comparison for the elastic crankshaft mechanism". Proceedings of the 2nd International Operational Modal Analysis Conference, Copenhagen, Denmark, April.
17 Friswell, M.I. (2007), "Damage identification using inverse methods", Philos. T. R. Soc. A, 365(1851), 393-410. https://doi.org/10.1098/rsta.2006.1930.   DOI
18 Hou, R., Xia, Y. and Zhou, X. (2018), "Structural damage detection based on l1 regularization using natural frequencies and mode shapes", Struct. Control Hlth. Monit., 25, e2107. https://doi.org/10.1002/stc.2107.   DOI
19 Huang, Q., Xu, Y.L., Li, J.C., Su, Z.Q. and Liu, H.J. (2012), "Structural damage detection of controlled building structures using frequency response functions", J. Sound Vib., 331(15), 3476-3492. https://doi.org/10.1016/j.jsv.2012.03.001.   DOI
20 Lee, U. and Shin, J. (2002), "A frequency response function-based structural damage identification method", Comput. Struct., 80(2), 117-132. https://doi.org/10.1016/S0045-7949(01)00170-5.   DOI
21 Liu, H.L., Yu, L., Luo, Z.W. and Pan, C.D. (2020) "Compressed sensing for moving force identification using redundant dictionaries", Mech. Syst. Signal Pr., 138, 106535. https://doi.org/10.1016/j.ymssp.2019.106535.   DOI
22 Li, X.Y., Wang, L.X., Law, S.S. and Nie, Z.H. (2017), "Covariance of dynamic strain responses for structural damage detection", Mech. Syst. Signal Pr., 95, 90-105. https://doi.org/10.1016/j.ymssp.2017.03.020.   DOI
23 Li, Y. and Chen, Y. (2013), "A review on recent development of vibration-based structural robust damage detection", Struct. Eng. Mech., 45(2), 159-168. https://doi.org/10.12989/sem.2013.45.2.159.   DOI
24 Liddle, A.R. (2007), "Information criteria for astrophysical model selection", Mon. Not. R. Astron. Soc., 377(1), L74-L78. https://doi.org/10.1111/j.1745-3933.2007.00306.x.   DOI
25 Pandey, A.K., Biswas, M. and Samman, M.M. (1991), "Damage detection from changes in curvature mode shapes", J. Sound Vib., 145(2), 321-332. https://doi.org/10.1016/0022-460X(91)90595-B.   DOI
26 Liu, L., Hua, W. and Lei, Y. (2018), "Real-time simultaneous identification of structural systems and unknown inputs without collocated acceleration measurements based on MEKF-UI", Measurement., 122, 545-553. https://doi.org/10.1016/j.measurement.2017.07.001.   DOI
27 Moughty, J.J. and Casas, J.R. (2017), "A state of the art review of modal-based damage detection in bridges: development, challenges, and solutions", Appl. Sci., 7(5), 510. https://doi.org/10.3390/app7050510.   DOI
28 O'Callahan, J. (1989), "System equivalent reduction expansion process (SEREP)". Proceedings of the 7th International Modal Analysis Conference, Las Vegas, U.S.A., February.
29 Shi, Z.Y., Law, S.S. and Zhang, L.M. (1998), "Structural damage localization from modal strain energy change", J. Sound Vib., 218(5), 825-844. https://doi.org/10.1006/jsvi.1998.1878.   DOI
30 Ratcliffe, C.P., (1997), "Damage detection using a modified laplacian operator on mode shape data", J. Sound Vib., 204(3), 505-517. https://doi.org/10.1006/jsvi.1997.0961.   DOI
31 Vahidi, M., Vahdani, S., Rahimian, M., Jamshidi, N. and Kanee, A.T. (2019), "Evolutionary-base finite element model updating and damage detection using modal testing results", Struct. Eng. Mech., 70(3), 339-350. https://doi.org/10.12989/sem.2019.70.3.339.   DOI
32 Yan, W.J. and Katafygiotis, L.S. (2019), "An analytical investigation into the propagation properties of uncertainty in a two-stage fast Bayesian spectral density approach for ambient modal analysis", Mech. Syst. Signal Pr., 118, 503-533. https://doi.org/10.1016/j.ymssp.2018.08.047.   DOI