Browse > Article
http://dx.doi.org/10.12989/sem.2021.79.6.683

Modal parameter estimation of civil structures based on improved variational mode decomposition  

Zhi, Lun-hai (College of Civil Engineering, Hefei University of Technology)
Hu, Feng (College of Civil Engineering, Hefei University of Technology)
Zhao, Chunfeng (College of Civil Engineering, Hefei University of Technology)
Wang, Jingfeng (College of Civil Engineering, Hefei University of Technology)
Publication Information
Structural Engineering and Mechanics / v.79, no.6, 2021 , pp. 683-697 More about this Journal
Abstract
This paper proposes an improved variational mode decomposition (IVMD) algorithm for structural modal parameter estimation based on non-stationary responses. In this improved VMD, the mean envelope entropy (MEE) and particle swarm optimization (PSO) are first employed to determine the optimal decomposition parameters for the subsequent VMD analysis. Then the VMD algorithm is used to decompose the non-stationary data into a number of intrinsic mode functions (IMFs). After obtaining the IMFs based on the IVMD, structural modal parameters such as natural frequencies and damping ratios of civil structures can be determined by using Natural Excitation Technique (NExT) and Direct Interpolating approach (DI). The feasibility and accuracy of the proposed procedure are evaluated by both numerical and full-scale examples. The natural frequencies and damping ratios are successfully identified from the vibration responses with high noise and non-stationary characteristics. The results of this study illustrate that the proposed procedure provides a powerful approach to identify the modal parameters of civil structures using non-stationary responses.
Keywords
damping ratios; improved variational mode decomposition; modal parameter estimation; natural frequencies; non-stationary;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Li, Q.S. and Wu, J.R. (2007), "Time-frequency analysis of typhoon effects on a 79-storey tall building", J. Wind Eng. Indus. Aerodyn., 95(12), 1648-1666. https://doi.org/10.1016/j.jweia.2007.02.030.   DOI
2 Li, Q.S., Zhi, L.H., Yi, J., To, A. and Xie, J.M. (2014a), "Monitoring of typhoon effects on a super-tall building in Hong Kong", Struct. Control Hlth. Monit., 21(6), 926-949. https://doi.org/10.1002/stc.1622.   DOI
3 Bendat, J.S. and Piersol, A.G. (2010), Random Data: Analysis and Measurement Procedures, 4th Edition, John Wiley & Sons, New York, USA.
4 Wang, Y.X., Markert, R., Xiang, J.W. and Zheng, W.G. (2015), "Research on variational mode decomposition and its application in detecting rub-impact fault of the rotor system", Mech. Syst. Signal Pr., 60-61, 243-251. https://doi.org/10.1016/j.ymssp.2015.02.020.   DOI
5 Shi, Z.Y. and Law, S.S. (2007), "Identification of linear time-varying dynamical systems using Hilbert transform and empirical mode decomposition method", J. Appl. Mech., 74(2), 223-230. https://doi.org/10.1115/1.2188538.   DOI
6 Soyoz, S. and Feng, M.Q. (2009), "Long-term monitoring and identification of bridge structural parameters", Comput. Aid. Civil Infrastr. Eng., 24(2), 82-92. https://doi.org/10.1111/j.1467-8667.2008.00572.x.   DOI
7 Sun, J., Xiao, Q., Wen, J. and Wang, F. (2014), "Natural gas pipeline small leakage feature extraction and recognition based on LMD envelope spectrum entropy and SVM", Measure., 55, 434-443. https://doi.org/10.1016/j.measurement.2014.05.012.   DOI
8 Sweeney, K.T., McLoone, S.F. and Ward, T.E. (2013), "The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique", IEEE Tran. Biomed. Eng., 60(1), 97-105. https://doi.org/10.1109/TBME.2012.2225427.   DOI
9 Wang, J.L. and Li, Z.J. (2013), "Extreme-point symmetric mode decomposition method for data analysis", Adv. Adapt. Data Anal., 5(3), 1137-1137. https://doi.org/10.1142/S1793536913500155.   DOI
10 Elegbede, C. (2005), "Structural reliability assessment based on particles swarm optimization", Struct. Saf., 27, 171-186. https://doi.org/10.1016/j.strusafe.2004.10.003.   DOI
11 Bossea, A., Taskerb, F. and Fisherc, S. (1998), "Real-time modal parameter estimation using subspace methods: Applications", Mech. Syst. Signal Pr., 12(6), 809-823. https://doi.org/10.1006/mssp.1998.0162.   DOI
12 Wu, Z. and Huang, N.E. (2009), "Ensemble empirical mode decomposition: A noise-assisted data analysis method", Adv. Adapt. Data Anal., 1(1), 1-41. https://doi.org/10.1142/S1793536909000047.   DOI
13 Yan, X., Jia, M. and Xiang, L. (2016), "Compound fault diagnosis of rotating machinery based on ovmd and a 1.5-dimension envelope spectrum", Measure. Sci. Technol., 27(7), 075002. https://doi.org/10.1088/0957-0233/27/7/075002.   DOI
14 Yang, J.N., Lei, Y., Pan, S.W. and Huang, N. (2003a), "System identification of linear structures based on Hilbert-Huang spectral analysis, Part 1: normal models", Earthq. Eng. Struct. Dyn., 32(9), 1443-1467. https://doi.org/10.1002/eqe.287.   DOI
15 Ai, T.J. and Kachitvichyanukul, V. (2009), "A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery", Comput. Oper. Res., 36(5), 1693-1702. https://doi.org/10.1016/j.cor.2008.04.003.   DOI
16 Ibrahim, S.R. (1977), "Random decrement technique for modal identification of structures", J. Spacecraf. Rocket., 14(11), 696-700. https://doi.org/10.2514/3.57251.   DOI
17 Rato, R.T., Ortigueira, M.D. and Batista, A.G. (2008), "On the HHT, its problems, and some solutions", Mech. Syst. Signal Pr., 22(6), 1374-1394. https://doi.org/10.1016/j.ymssp.2007.11.028.   DOI
18 Li, Q.S., Fang, J.Q., Jeary, A.P. and Wong, C.K. (1998), "Full scale measurement of wind effects on tall buildings", J. Wind Eng. Indus. Aerodyn., 74-76, 741-750. https://doi.org/10.1016/S0167-6105(98)00067-1.   DOI
19 Ardakani, A.J., Ardakani, F.F. and Hosseinian, S.H. (2008), "A novel approach for optimal chiller loading using particle swarm optimization", Energy Build., 40(12), 2177-2187. https://doi.org/10.1016/j.enbuild.2008.06.010.   DOI
20 Bagheri, A., Ozbulut, O.E. and Harris, D.K. (2018), "Structural system identification based on variational mode decomposition", J. Sound Vib., 417, 182-197. https://doi.org/10.1016/j.jsv.2017.12.014.   DOI
21 Liu, W., Cao, S. and Chen, Y. (2016), "Applications of variational mode decomposition in seismic time-frequency analysis", Geophys., 81(5), 365-378. https://doi.org/10.1190/geo2015-0489.1.   DOI
22 Li, Q.S., Zhi, L.H., Tuan, A.Y., Kao, S.H., Su, S.C. and Wu, C.F. (2011), "Dynamic behavior of Taipei 101 Tower: field measurement and numerical analysis", J. Struct. Eng., ASCE, 137(1), 143-155. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000264.   DOI
23 Li, Y., Cheng, G., Liu, C. and Chen, X.H. (2018), "Study on planetary gear fault diagnosis based on variational mode decomposition and deep neural networks", Measure., 130, 94-104. https://doi.org/10.1016/j.measurement.2018.08.002.   DOI
24 Li, Y., Zhang, J.W. and Li, Q.S. (2014b), "Experimental investigation of characteristics of torsional wind loads on rectangular tall buildings", Struct. Eng. Mech., 49(1), 129-145. https://doi.org/10.12989/sem.2014.49.1.129.   DOI
25 Yan, X. and Jia, M. (2019), "Application of csa-vmd and optimal scale morphological slice bispectrum in enhancing outer race fault detection of rolling element bearings", Mech. Syst. Signal Pr., 122, 56-86. https://doi.org/10.1016/j.ymssp.2018.12.022.   DOI
26 Lv, Z., Tang, B., Zhou, Y. and Zhou, C. (2016), "A novel method for mechanical fault diagnosis based on variational mode decomposition and multikernel support vector machine", Shock Vib., 2016, 1-11. https://doi.org/10.1155/2016/3196465.   DOI
27 Ni, P.H., Li, J., Hao, H., Xia, Y., Wang, X.Y., Lee, J.M. and Jung, K.H. (2018), "Time-varying system identification using variational mode decomposition", Struct. Control Hlth. Monit., 25(6), e2175. https://doi.org/10.1002/stc.2175.   DOI
28 Farrar, C.R. and James III, G.H. (1997), "System identification from ambient vibration measurements on a bridge", J. Sound Vib., 205(1), 1-18. https://doi.org/10.1006/jsvi.1997.0977.   DOI
29 Chen, J., Xu, Y.L. and Zhang, R.C. (2004), "Modal parameter identification of Tsing Ma suspension bridge under Typhoon Victor: EMD-HT method", J. Wind Eng. Indus. Aerodyn., 92, 805-827. https://doi.org/10.1016/j.jweia.2004.04.003.   DOI
30 Dragomiretskiy, K. and Zosso, D. (2014), "Variational Mode Decomposition", IEEE Tran. Signal Pr., 62(3), 531-544. https://doi.org/10.1109/TSP.2013.2288675.   DOI
31 Gilles, J. (2013), "Empirical wavelet transform", IEEE Tran. Signal Pr., 61(16), 3999-4010. https://doi.org/10.1109/TSP.2013.2265222.   DOI
32 Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C. and Liu, H.H. (1998), "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Proc. Roy. Soc. London, Ser. A: Math. Phys. Eng. Sci., 454, 903-995. https://doi.org/10.1098/rspa.1998.0193.   DOI
33 Li, F.H., Li, R., Tian, L.L., Chen, L. and Liu, J. (2019), "Data-driven time-frequency analysis method based on variational mode decomposition and its application to gear fault diagnosis in variable working conditions", Mech. Syst. Signal Pr., 116, 462-479. https://doi.org/10.1016/j.ymssp.2018.06.055.   DOI
34 Nuttall, A.H. and Bedrosian, E. (1996), "On the quadrature approximation to the Hilbert transform of modulated signals", Proc. IEEE, 54(10), 1458-1459. https://doi.org/10.1109/PROC.1966.5138.   DOI
35 Yang, J.N., Lei, Y., Pan, S.W. and Huang, N. (2003b), "System identification of linear structures based on Hilbert-Huang spectral analysis, Part 2: complex models", Earthq. Eng. Struct. Dyn., 32(10), 1533-1554. https://doi.org/10.1002/eqe.288.   DOI
36 Zhang, G., Liu, H.C., Zhang, J.B., Yan, Y., Zhang, L., Wu, C., Hua, X. and Wang Y.Q. (2019), "Wind power prediction based on variational mode decomposition multi-frequency combinations", J. Mod. Power Syst. Clean Energy, 7(2), 281-288. https://doi.org/10.1007/s40565-018-0471-8.   DOI
37 Zhang, M.J. and Xu, F.Y. (2019), "Variational mode decomposition based modal parameter identification in civil engineering", Front. Struct. Civil Eng., 13(5), 1082-1094. https://doi.org/10.1007/s11709-019-0537-3.   DOI
38 Jacobsen, N.J., Andersen, P. and Brincker, R. (2006), "Using enhanced frequency domain decomposition as a robust technique to harmonic excitation in operational modal analysis", Proceedings of ISMA2006: International Conference on Noise & Vibration Engineering, Leuven, Belgium.
39 Lahmiri, S. (2015), "Comparing variational and empirical mode decomposition in forecasting day-ahead energy prices", IEEE Syst. J., 11(3), 1907-1910. https://doi.org/10.1109/JSYST.2015.2487339.   DOI
40 Kennedy, J. and Eberhart, R.C. (1995), "Particle swarm optimization", Proceedings of the IEEE International Conference on Neural Networks, 1942-1948. https://doi.org/10.1109/ICNN.1995.488968.   DOI