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http://dx.doi.org/10.12989/smm.2019.6.3.237

Damage assessment of shear-type structures under varying mass effects  

Do, Ngoan T. (Department of Civil and Environmental Engineering, University of Alberta)
Mei, Qipei (Department of Civil and Environmental Engineering, University of Alberta)
Gul, Mustafa (Department of Civil and Environmental Engineering, University of Alberta)
Publication Information
Structural Monitoring and Maintenance / v.6, no.3, 2019 , pp. 237-254 More about this Journal
Abstract
This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.
Keywords
structural health monitoring; damage detection; time series analysis; structural dynamics;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 Box, G.E., Jenkins, G.M. and Reinsel, G.C. (2016), Time Series Analysis: Forecasting and Control. Prentice-Hall, Upper Saddle River, NJ.
2 Celik, O., Terrell, T., Necati, C.F. and Gul, M. (2018), "Sensor clustering technique for practical structural monitoring and maintenance", Struct. Monit. Maint., 5(2), 273-295. https://doi.org/10.12989/smm.2018.5.2.273.   DOI
3 Devin, A. and Fanning, P.J. (2012), "The evolving dynamic response of a four storey reinforced concrete structure during construction", Shock Vib., 19(5), 1051-1059. https://doi.org/10.1155/2012/260926.   DOI
4 Fan, W. and Qiao, P. (2011), "Vibration-based damage identification methods: A review and comparative study", Struct. Health Monit., 1(2), 83-111. https://doi.org/10.1088/0964-1726/1/2/002.   DOI
5 Figueiredo, E., Park, G.H., Farinholt, K.M., Farrar, C.R. and Lee, J.R. (2012), "Use of time-series predictive models for piezoelectric active-sensing in structural health monitoring applications", J. Vib. Acoust., 134 (4), 041014-041014. https://doi.org/10.1115/1.4006410.   DOI
6 Gul, M. and Catbas, F.N. (2009), "Statistical pattern recognition for structural health monitoring using time series modeling: Theory and experimental verifications", Mech. Syst. Signal Pr., 23, 2192-2204. https://doi.org/10.1016/j.ymssp.2009.02.013.   DOI
7 Gul, M. and Catbas, F.N. (2011), "Structural health monitoring and damage assessment using a novel time series analysis methodology with sensor clustering", J. Sound Vib., 330(6), 1196-1210. https://doi.org/10.1016/j.jsv.2010.09.024.   DOI
8 Gul, M. and Catbas, F.N. (2008), "A new methodology for identification, localization and quantification of damage by using time series modeling", Proceedings of the 28th International Modal Analysis Conference (IMAC XXVI), Florida.
9 He, K. and Zhu, W.D. (2011), "A vibration-based structural damage detection method and its applications to engineering structures", Int. J. Smart Nano Mater., 2(3), 194-218. https://doi.org/10.1080/19475411.2011.594105.   DOI
10 Kuwabara, M., Yoshitomi, S. and Takewaki, I. (2013), "A new approach to system identification and damage detection of high-rise buildings", Struct. Control Health Monit., 20, 703-727. https://doi.org/10.1002/stc.1486.   DOI
11 Levy, H. and Lessman, F. (1961), Finite Difference Equations, Courier Corporation.
12 Li, S. and Wu, Z. (2007), "Development of distributed long-gage fiber optic sensing system for structural health monitoring", Struct. Health Monit., 6(2), 133-143. https://doi.org/10.1177/1475921706072078.   DOI
13 Loh, C.H., Chen, C.H. and Hsu, T.Y. (2011), "Application of advanced statistical methods for extracting long-term trends in static monitoring data from an arch dam", Struct. Health Monit., 10(6), 587-601.   DOI
14 Lu, Y. and Gao, F. (2005), "A novel time-domain auto-regressive model for structural damage diagnosis", J. Sound Vib., 283(3), 1031-1049.   DOI
15 Mehdi, S. (2010), "Vibration serviceability of a building floor structure. I: Dynamic testing and computer modeling", J. Perform. Constr. Fac., 24(6), 497-507. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000134.   DOI
16 Mei, Q. and Gul, M. (2015), "Novel sensor clustering - Based approach for simultaneous detection of stiffness and mass changes using output-only data", J. Struct. Eng., 141(10), 04014237. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001218.   DOI
17 Peter Carden, E. and Brownjohn, J.M.W. (2008), "ARMA modelled time-series classification for structural health monitoring of civil infrastructure", Mech. Syst. Signal Pr., 22(2), 295-314. https://doi.org///dx.doi.org/10.1016/j.ymssp.2007.07.003.   DOI
18 Montgomery, D.C., Jennings, C.L. and Kulahci, M. (2008), Introduction to Time Series Analysis and Forecasting. Hoboken, New Jersey : Wiley-Interscience, 2008.
19 Nguyen, C.U., Huynh, T.C. and Kim, J.T. (2018), "Vibration-based damage detection in wind turbine towers using artificial neural networks", Struct. Monit. Maint., 5(4), 507-519. https://doi.org/10.12989/smm.2018.5.4.507.   DOI
20 Omenzetter, P. and Brownjohn, J.M.W. (2006), "Application of time series analysis for bridge monitoring", Smart Mater. Struct., 15(1), 129-129. .   DOI
21 Takewaki, I. and Nakamura, M. (2000), "Stiffness-damping simultaneous identification using limited earthquake records", Earthq. Eng. Struct. D., 29, 1219-1238.   DOI
22 Roy, K., Bhattacharya, B. and Ray-Chaudhuri, S. (2015), "ARX model-based damage sensitive features for structural damage localization using output-only measurements", J. Sound Vib., 349, 99-122. https://doi.org/10.1016/j.jsv.2015.03.038.   DOI
23 Rytter, A. (1993), "Vibration Based Inspection of Civil Engineering Structures, 1993", Ph. D. dissertation.
24 Shahidi, S.G., Nigro, M.B., Pakzad, S.N. and Pan, Y. (2015), "Structural damage detection and localisation using multivariate regression models and two-sample control statistics", Struct. Infrastruct. Eng., 11(10), 1277-1293-1277-1293. https://doi.org/10.1080/15732479.2014.949277.   DOI
25 Siebel, T., Friedmann, A., Koch, M. and Mayer, D. (2012), "Assessment of mode shape-based damage detection methods under real operational conditions", Proceedings of the 6th European Workshop on Structural Health Monitoring.
26 Xi, P.S., Ye, X.W., Jin, T. and Chen, B. (2018), "Structural performance monitoring of an urban footbridge", Struct. Monit.Maint., 5(1), 129-150. https://doi.org/10.12989/smm.2018.5.1.129.
27 Soman, R., Kyriakides, M., Onoufriou, T. and Ostachowicz, W. (2017), "Numerical evaluation of multi-metric data fusion based structural health monitoring of long span bridge structures", Struct. Infrastruct. Eng., 1-12. https://doi.org/10.1080/15732479.2017.1350984.
28 Sony, S., Laventure, S. and Sadhu, A. (2019), "A literature review of next-generation smart sensing technology in structural health monitoring", Struct. Control Health Monit., 26(3), https://doi.org/10.1002/stc.2321.
29 Takewaki, I. and Nakamura, M. (2005), "Stiffness-damping simultaneous identification under limited observation", J. Eng. Mech. -ASCE, 131, 1027-1035. https://doi.org/10(1027).   DOI
30 Zhang, D. and Johnson, E.A. (2013a), "Substructure identification for shear structures I: substructure identification method", Struct. Control Health Monit., 20, 804-820. https://doi.org/10.1002/stc.1497.   DOI
31 Zhang, D. and Johnson, E.A. (2013b), "Substructure identification for shear structures II: Controlled substructure identification", Struct. Control Health Monit., 20, 821-834. https://doi.org/10.1002/stc.1498.   DOI
32 Bao, C.X., Hao, H. and Li, Z.X. (2013), "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.   DOI
33 Agarwal, S. and Mitra, M. (2014), "Lamb wave based automatic damage detection using matching pursuit and machine learning", Smart Mater. Struct., 23(8), https://doi.org/10.1088/0964-1726/23/8/085012.
34 Assi, R., Youance, S., Bonne, A. and Nollet, M.J. (2016), "Effect of non-structural components on the modal properties of buildings using ambient vibration testing", Proceedings of the Annual Conference of the Canadian Society for Civil Engineering.
35 Balageas, D., Fritzen, C.P. and Guemes, A. (2006), Structural Health Monitoring. Wiley Online Library.
36 Bas, S., Apaydin, N.M., Ilki, A. and Catbas, F.N. (2017), "Structural health monitoring system of the long-span bridges in Turkey", Struct. Infrastruct. Eng., 1-20. https://doi.org/10.1080/15732479.2017.1360365.
37 Bighamian, R. and Mirdamadi, H.R. (2013), "Input/output system identification of simultaneous mass/stiffness damage assessment using discrete-time pulse responses, differential evolution algorithm, and equivalent virtual damped SDOF", Struct. Control Health Monit., 20, 576-592. https://doi.org/10.1002/stc.516.   DOI