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http://dx.doi.org/10.12989/sss.2013.12.3_4.309

Online damage detection using pair cointegration method of time-varying displacement  

Zhou, Cui (Faculty of Infrastructure Engineering, Dalian University of Technology)
Li, Hong-Nan (Faculty of Infrastructure Engineering, Dalian University of Technology)
Li, Dong-Sheng (Faculty of Infrastructure Engineering, Dalian University of Technology)
Lin, You-Xin (Guangdong Electrical Company)
Yi, Ting-Hua (Faculty of Infrastructure Engineering, Dalian University of Technology)
Publication Information
Smart Structures and Systems / v.12, no.3_4, 2013 , pp. 309-325 More about this Journal
Abstract
Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.
Keywords
structural health monitoring; damage detection; environmental variable; pair cointegration; time series; data-based model;
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1 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   ScienceOn
2 Monson, H. (1996), Statistical digital signal processing and modeling, John Wiley & Sons, Manhattan.
3 Moorty, S.S. and Roeder, C.W. (1992), "Temperature-dependent bridge movements", J. Struct. Eng.- ASCE, 118(4), 1090-1105.   DOI
4 Peeters, B. and De Roeck, G. (2000), "One year monitoring of the Z24-bridge: Environmental influences versus damage events", Proceedings of the IMAC-XVIII, San Antonio, TX.
5 Sohn, H. (2007), "Effects of environmental and operational variability on structural health monitoring", Philos. T. R. Soc. A., 365, 539-560.   DOI   ScienceOn
6 Wang, Y.L., Liu, X.L. and Fang, C.Q. (2012), "Damage detection of bridges by using displacement data of two symmetrical points", J. Perform. Constr. Fac., 25(3), 300-311.
7 Dickey, D.A. and Fuller, W.A. (1979), "Distributions of the estimators for auto-regressive time series with a unit root", J. Am. Stat. Assoc., 74, 427-431.
8 Dickey, D.A. and Fuller, W. (1981), "Likelihood ratio statistics for autoregressive time series with a unit root", Econometrica, 49, 1057-1072.   DOI   ScienceOn
9 Doebling, S.W. and Farrar, C.R. (1997), "Using statistical analysis to enhance modal-based damage identification", Proceedings of the DAMAS 97: structural damage assessment using advanced signal processing procedures, University of Sheffield, UK.
10 Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based identification methods", Shock Vib., 30(2), 91-105.   DOI   ScienceOn
11 Engle, R.F. and Granger, C.W.J. (1987), "Cointegration and error-correction: representation, estimation and testing", Econometrica, 55, 251-276.   DOI   ScienceOn
12 Fan, W. and Qiao, P.Z. (2011), "Vibration-based damage identification methods: a review and comparative study", Struct Health Monit., 10(1), 83-111.   DOI   ScienceOn
13 Figueiredo, E., Park, G., Farrar, C.R., Worden, K. and Figueiras, J. (2010), "Machine learning algorithms for damage detection under operational and environmental variability", Struct Health Monit., 10(6), 559-572.
14 Fuller, W. (1996), Introduction to statistical time series, Wiley-Interscience, New York.
15 Fritzen, C.R., Mengelkamp, G. and Guemes, A. (2003), "Elimination of temperature effects on damage detection within a smart structure concept", Proceedings of the 4th Int. Workshop on Structural Health Monitoring, Stanford University, CA.
16 Gao, T. M. (2009), Econometrical analysis methods and modelling, Qinghua Press, Beijing, China.
17 Ghrib, F., Li, L. and Wilbur, P. (2012), "Damage identification of Euler-Bernoulli beams using static responses", J. Eng. Mech. - ASCE., 135(5), 405-415.
18 Askegaard, V. and Mossing, P. (1988), "Long term observation of RC-bridge using changes in natural frequencies", Nord. Concrete Federation, 7, 20-27.
19 Box, G.E.P., Jenkins, G.M. and Reinsel, G.C. (1994), Time series analysis-forecasting and control, 3rd Ed, Prentice-Hall: Englewood Cliffs, NJ.
20 Chen, Q., Kruger, U. and Leung, A. (2009), "Cointegration testing method for monitoring nonstationary processes", Ind. Eng. Chem. Res., 48(7), 3533-3543.   DOI   ScienceOn
21 Cross, E.J., Worden, K. and Chen, Q. (2011), "Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data", Proc. R. Soc. A., 467, 2712-2732.   DOI   ScienceOn
22 Code for Design of Concrete Structures (GB 500102002), Beijing, 2002.
23 Dewangan, U.K. (2011), "Structural damage existence prediction with few measurements", Int. J. Eng. Sci. Technol., 3 (10), 7587-7597.
24 Lee, E.T. and Eun, H.C. (2008), "Damage detection of damaged beam by constrained displacement curvature", J. Mech. Sci. Technol., 22(6), 1111-1120.   DOI   ScienceOn
25 Yan, A.M., Kerschen, G., De Boe, P. and Golinval, J.C. (2005), "Structural damage diagnosis under varying environmental conditions - part I: a linear analysis", Mech. Syst. Signal Pr., 19, 847-864.   DOI   ScienceOn
26 Zhou, H.F, Ni, Y.Q. and Ko, J.M. (2011), "Elimination temperature effect in vibration-based structural damage detection", J. Eng. Mech.- ASCE, 137(12), 785-796.   DOI   ScienceOn
27 Johansen, S. (1988), "Statistical analysis of cointegrating vectors", J. Econom. Dyn. Control, 12(2-3), 231-254.   DOI   ScienceOn
28 Johansen, S. and Juselius, K. (1990), "Maximum likelihood estimation and inference on cointegration with applications to the demand for money", Oxford Bull. Econom. Stat., 52(2), 169-210.   DOI
29 Kim, C.Y., Jung, D.S., Kim, N.S., Kwon, S.D. and Feng, M.Q. (2003), "Effect of vehicle weight on natural frequencies of bridges measured from traffic-induced vibration", Earthq. Eng. Eng. Vib., 2(1), 109-115.   DOI   ScienceOn
30 Li, Y.H. (2009). Study on structural modeling and damage identification methods of cracked beams, M.S. thesis, Dalian Univ. of Technol., Dalian, China.