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http://dx.doi.org/10.12989/eas.2017.12.6.673

Three-dimensional structural health monitoring based on multiscale cross-sample entropy  

Lin, Tzu Kang (Department of Civil Engineering, National Chiao Tung University)
Tseng, Tzu Chi (Department of Civil Engineering, National Chiao Tung University)
Lainez, Ana G. (Department of Civil Engineering, National Chiao Tung University)
Publication Information
Earthquakes and Structures / v.12, no.6, 2017 , pp. 673-687 More about this Journal
Abstract
A three-dimensional; structural health monitoring; vertical; planar; cross-sample entropy; multiscaleA three-dimensional structural health monitoring (SHM) system based on multiscale entropy (MSE) and multiscale cross-sample entropy (MSCE) is proposed in this paper. The damage condition of a structure is rapidly screened through MSE analysis by measuring the ambient vibration signal on the roof of the structure. Subsequently, the vertical damage location is evaluated by analyzing individual signals on different floors through vertical MSCE analysis. The results are quantified using the vertical damage index (DI). Planar MSCE analysis is applied to detect the damage orientation of damaged floors by analyzing the biaxial signals in four directions on each damaged floor. The results are physically quantified using the planar DI. With progressive vertical and planar analysis methods, the damaged floors and damage locations can be accurately and efficiently diagnosed. To demonstrate the performance of the proposed system, performance evaluation was conducted on a three-dimensional seven-story steel structure. According to the results, the damage condition and elevation were reliably detected. Moreover, the damage location was efficiently quantified by the DI. Average accuracy rates of 93% (vertical) and 91% (planar) were achieved through the proposed DI method. A reference measurement of the current stage can initially launch the SHM system; therefore, structural damage can be reliably detected after major earthquakes.
Keywords
three-dimensional; structural health monitoring; vertical; planar; cross-sample entropy; multiscale;
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1 Chang P.C. Flatau A. and Liu S.C. (2003) "Review paper: health monitoring of civil infrastructure" Struct. Hlth. Monit., 2(3), 257-267.   DOI
2 Chen Z. Fang H. Ke X. and Zeng Y. (2016) "A new method to identify bridge bearing damage based on radial basis function neural network" Earthq. Struct., 11(5), 841-859.   DOI
3 Costa, M., Goldberger, A.L. and Peng, C.K. (2002), "Multiscale entropy analysis of complex physiologic time series" Phys. Rev. Lett., 89(6), 068102.   DOI
4 Costa M. Goldberger A.L. and Peng C.K. (2005) "Multiscale entropy analysis of biological signals" Phys. Rev. E., 71(2), 021906.   DOI
5 Kolmogorov A.N. (1958) "New metric invariant of transitive dynamical systems and endomorphisms of lebesgue spaces" Doklady Russian Acad. Sci., 119, 861-864.
6 Doebling, S.W., Farrar C.R. and Prime M.B. (1998) "A summary review of vibration-based damage identification" Shock Vib. Digest, 30(2), 91-105.   DOI
7 Fabris C. De Colle W. and Sparacino G. (2013) "Voice disorders assessed by (cross-) sample entropy of electroglottogram and microphone signals" Biomed. Sign. Proc., 8(6), 920-926.   DOI
8 Friswell M.I. Penny J.E.T. and Garvey S.D. (1997) "Parameter subset selection in damage location" Inverse Probl. Eng., 5(3), 189-215.   DOI
9 Lam H.F. and Yang J.H. (2015) "Bayesian structural damage detection of steel towers using measured modal parameters" Earthq. Struct., 8(4), 935-956.   DOI
10 Lin T.K. and Liang J.C. (2015) "Application of multi-scale (cross-) sample entropy for structural health monitoring" Smart Mater. Struct., 24(8), 085003.   DOI
11 Liu H. and Han M. (2014) "A fault diagnosis method based on local mean decomposition and multi-scale entropy for roller bearings" Mech. Mach. Theory, 75, 67-78.   DOI
12 Maeck, J., Wahab, M.A., Peeters, B., De Roeck, G., De Visscher, J., De Wilde, W.P., Ndambi, J.M. and Vantomme, J. (2000), "Damage identification in reinforced concrete structures by dynamic stiffness determination" Eng. Struct., 22(10), 1339-1349.   DOI
13 Shannon C.E. (1948) "A mathematical theory of communication" Bell Syst. Tech. J., 27, 379-423.   DOI
14 Pincus S.M. (1991) "Approximate entropy as a measure of system complexity" Proc. Natl. Acad. Sci. U.S.A., 88(6), 2297-2301.   DOI
15 Pincus S.M., Gladstone, I.M. and Ehrenkranz, R.A. (1991), "A regularity statistic for medical data analysis" J. Clin. Monit., 7(4), 335-345.   DOI
16 Richman J.S. and Moorman J.R. (2000) "Physiological timeseries analysis using approximate entropy and sample entropy" Am. J. Physiol. Heart Circ. Physiol., 278(6), H2039-2049.   DOI
17 Sinai Y.G. (1959) "On the notion of entropy of a dynamical system" Doklady Russian Acad. Sci., 124, 768-771.
18 Xie, H.B., Zheng, Y.P., Guo, J.Y. and Chen, X. (2010) "Crossfuzzy entropy: a new method to test pattern synchrony of bivariate time series" Inform. Sci., 180(9), 1715-1724.   DOI
19 Zhang, L., Xiong, G., Liu, H., Zou, H. and Guo, W. (2010), "Bearing fault diagnosis using multi-scale entropy and adaptive neuro-fuzzy inference" Exp. Syst. Appl., 37(8), 6077-6085.   DOI