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Mode identifiability of a multi-span cable-stayed bridge utilizing stabilization diagram and singular values
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  • Journal title : Smart Structures and Systems
  • Volume 17, Issue 3,  2016, pp.391-411
  • Publisher : Techno-Press
  • DOI : 10.12989/sss.2016.17.3.391
 Title & Authors
Mode identifiability of a multi-span cable-stayed bridge utilizing stabilization diagram and singular values
Goi, Y.; Kim, C.W.;
 Abstract
This study investigates the mode identifiability of a multi-span cable-stayed bridge in terms of a benchmark study using stabilization diagrams of a system model identified using stochastic subspace identification (SSI). Cumulative contribution ratios (CCRs) estimated from singular values of system models under different wind conditions were also considered. Observations revealed that wind speed might influence the mode identifiability of a specific mode of a cable-stayed bridge. Moreover the cumulative contribution ratio showed that the time histories monitored during strong winds, such as those of a typhoon, can be modeled with less system order than under weak winds. The blind data Acc 1 and Acc 2 were categorized as data obtained under a typhoon. Blind data Acc 3 and Acc 4 were categorized as data obtained under wind conditions of critical wind speeds around 7.5 m/s. Finally, blind data Acc 5 and Acc 6 were categorized as data measured under weak wind conditions.
 Keywords
benchmark study;cable-stayed bridge;cumulative contribution ratio;operational modal identification;
 Language
English
 Cited by
1.
Investigation of Operational Modal Identification of a Cable-Stayed Bridge Based on Bayesian Estimation Considering Stochastic Uncertainty, Journal of Japan Society of Civil Engineers, Ser. A2 (Applied Mechanics (AM)), 2016, 72, 2, I_751  crossref(new windwow)
 References
1.
Akaike, H. (1973), "Information theory and extension of the maximum likelihood principle", Proceedings of the 2nd Int. Symp. on Information Theory, Petrov, B. N. and Csaki. F., Tsahkadsov, Armenia, USSR.

2.
Bergermann, R. and Schlaich, M. (1996), "Ting Kau Bridge, Hong Kong", Struct. Eng. Int., 6(3), 152-154. crossref(new window)

3.
Brincker, R., Zhang, L. and Andersen, P. (2000), "Modal identification from ambient response using frequency domain decomposition", IMAC XVIII, San Antonio, USA.

4.
Chang, K.C., Kim, C.W. and Kitauchi, S. (2013), "Stability diagram aided multivariate AR analysis for identifying the modal parameters of al steel truss bridge subjected to artificial damage", Proceedings of the 13th East Asia-Pacific Conf. on Structural Eng. and Constr. (EASEC-13), September 11-13, Sapporo, Japan.

5.
Daniels, R.W. (1974), Approximation Methods for Electronic Filter Design, McGraw-Hill, New York.

6.
Deraemaeker, A., Reynders, E., De Roeck, G. and Kullaa, J. (2007), "Vibration-based structural health monitoring using output-only measurements under changing environment", Mech. Syst. Signal Pr., 22(1), 34-56.

7.
He, X. and De Roeck, G. (1997), "System identification of mechanical structures by a high-order multivariate autoregressive model", Comput. Struct., 64(1-4), 341-351. crossref(new window)

8.
Heylen, W., Lammens, S. and Sas, P. (1997), Modal Analysis Theory and Testing, K.U. Leuven, Belgium.

9.
Kim, C.W. and Chang, K.C. (2014a), "A field experiment on a simply supported steel truss bridge for damage detection utilizing statistical patterns of identified modal parameters", Life-Cycle of Structural Systems: Design, Assessment, Maintenance and Management, (Eds., Furuta, Frangopol, Akiyama), Proceedings of the 4thInt. Symp. On Life-Cycle Civil Eng.,, Nov. 16-19, 2014, Tokyo, Japan.

10.
Kim, C.W., Isemoto, R., Sugiura, K. and Kawatani, M. (2013), "Structural fault detection of bridges based on linear system parameter and MTS method", J. of JSCE, 1(1), 32-43. crossref(new window)

11.
Kim, C.W., Kitauchi, S., Sugiura, K. and Kawatani, M. (2014b), "Utilizing reproduced autoregressive model for damage detection of real truss bridges", Life-Cycle of Structural Systems: Design, Assessment, Maintenance and Management, (Eds., Furuta, Frangopol, Akiyama), Proceedings of the 4th Int. Symp. On Life-Cycle Civil Eng., Nov. 16-19, 2014, Tokyo, Japan.

12.
Ko, J.M. and Ni, Y.Q. (2005), "Technology developments in structural health monitoring of large-scale bridges", Eng. Struct., 27(12), 1715-1725. crossref(new window)

13.
Ni, Y.Q., Wang, Y.W. and Xia, Y.X. (2015), "Investigation of mode identifiability of a cable-stayed bridge: comparison from ambient vibration responses and from typhoon-induced dynamic responses", Smart Struct. Syst., 15(2), 447-468. crossref(new window)

14.
Peeters, B., Dammekens, F., Magalhaes, F., Van der Auweraer, H., and Cunha, A. (2006), "Multi-run Operational Modal analysis of the Guadiana Cable-stayed Bridge", Proceedings of the IMAC24, St. Louis, MO, January.

15.
Van Overschee, P. and De Moor, B (1996), Subspace Identification for Linear Systems, Kluwer Academic Publishers.

16.
Wenzel, H. and Pichler, D. (2006), Ambient Vibration Monitoring, John Wiley & Sons.

17.
Wong, K.Y. (2004), "Instrumentation and health monitoring of cable-supported bridges", Struct. Control Health Monit., 11(2), 91-124. crossref(new window)

18.
Zhang, Q.W. (2007), "Statistical damage identification for bridges using ambient vibration data", Comput. Struct., 85(7-8), 476-485. crossref(new window)