Sequential non-linear least-square estimation for damage identification of structures

International Journal of Non-Linear Mechanics

Volumn 41, Issue 1, 2006, Pages 124-140

  Yang, Jann N ^a   Huang, Hongwei ^a   Lin, Silian ^a  

^a University of California at Irvine   (United States)

Author keywords

Adaptive tracking; Damage detection; On line system identification; Sequential non linear least square estimation

Indexed keywords

COMPUTER SIMULATION; MONITORING; ONLINE SYSTEMS; SENSORS; STRUCTURE (COMPOSITION); VIBRATIONS (MECHANICAL);

ADAPTIVE TRACKING; DAMAGE DETECTION; EXTENDED KALMAN FILTER (EKF); SEQUENTIAL NON-LINEAR LEAST-SQUARE (SNLSE); SEQUENTIAL NON-LINEAR LEAST-SQUARE ESTIMATION; STRUCTURAL PARAMETERS;

LEAST SQUARES APPROXIMATIONS;

EID: 29144452437     PISSN: 00207462     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijnonlinmec.2005.06.006     Document Type: Article

References (17)

1. F.-K. Chang (Ed.), Structural Health Monitoring, DEStech Publ., Inc., Lancaster, PA, Proceedings of the Fourth International Workshop on Structural Health Monitoring, Stanford University, Stanford, CA, 2003.
2. S.W. Doebling, C.R. Farrar, and M.B. Prime A summary review of vibration-based damage identification methods Shock Vibration Digest 30 2 1998 91 105
3. J.W. Lin, R. Betti, A.W. Smyth, and R.W. Longman On-line Identification of nonlinear hysteretic structural systems using a variable trace approach Earthquake Eng. Struct. Dyn. 30 2001 1279 1303
4. A.W. Smyth, S.F. Masri, A.G. Chassiakos, and T.K. Caughey On-line parametric identification of mDOF nonlinear hysteretic systems ASCE J. Eng. Mech. 125 1999 133 142
5. J.N. Yang, and S. Lin On-line identification of nonlinear hysteretic structures using an adaptive tracking technique Int. J. Non-linear Mech. 39 2004 1481 1491
6. M. Hoshiya, and E. Saito Structural identification by extended Kalman filter ASCE J. Eng. Mech. 110 12 1984 1757 1771
7. M. Shinozuka, and R. Ghanem Structural system identification II: experimental verification ASCE J. Eng. Mech. 121 2 1995 265 273
8. O. Maruyama, M. Hoshiya, System identification of an experimental model by extended Kalman filter, Proceedings of Structural Safety and Reliability, ICOSSAR 2001, CD-ROM, 2001, 7pp.
9. T. Sato, and K. Takei Development of a Kalman filter with fading memory Proceedings of Structural Safety and Reliability ICOSSAR 1998 1998 387 394
10. T. Sato, R. Honda, T. Sakanoue, Application of adaptive Kalman filter to identify a five story frame structure using NCREE experimental data, Proceedings of Structural Safety and Reliability, ICOSSA 2001, CD-ROM, 2001, 7pp.
11. J.N. Yang, S. Lin, and L. Zhou Identification of parametric changes for structural health monitoring using an adaptive filtering technique, smart structures and materials 2004: sensors and smart structures technologies for civil, mechanical and aerospace systems Proc. SPIE 5391 2004 389 399
12. J.N. Yang, S. Lin, L. Zhou, An adaptive extended Kalman filter for structural system and damage identifications, J. Struct. Control Health Monitoring 12, 2005, in press.
13. J.N. Yang, and S. Lin Identification of parametric variations of structures based on least square estimation and adaptive tracking technique ASCE J. Eng. Mech. 131 3 2005 290 298
14. G.C. Goodwin, and K.S. Sin Adaptive Filtering, Prediction and Control 1984 Prentice-Hall Englewood Cliffs, NJ
15. Q. Xia, M.Y. Rao, and X. Shen Adaptive fading Kalman filter with an application Automatica 30 1994 1333 1338
16. E.A. Johnson, H.F. Lam, L.S. Katafygiotis, and J.L. Beck The Phase I IASC-ASCE structural health monitoring benchmark problem using simulated data ASCE J. Eng. Mech. 130 1 2004 3 15
17. Y.K. Wen Methods of random vibration for inelastic structures ASME Applied Mech. Rev. 42 2 1989 39 52