structural health monitoring; effects of environmental variations; local principal component analysis; bridge diagnosis
Abstract :
[en] It is well known that changes in vibration features of structures due to damage may be masked by the effects of environmental variations. This influence has to be eliminated in the structural health-monitoring process, especially when a long-term in situ monitoring is expected. In the companion paper [1] a linear method based on principal component analysis (PCA) has been proposed and has shown encouraging results for linear or even weakly non-linear cases. The present paper concerns a further extension of the proposed method to handle non-linear cases, which may be encountered in some complex structures. The method involves a two-step procedure, namely a clustering of the data space into several regions and then the application of PCA La each local region. The application of local PCA allows performing a piecewise linearisation of the non-linear problem. A close look at the choice of the distortion function used in data clustering leads to two new clustering strategies. Whereas the first strategy is specifically suitable for the application treated in this paper, the second one is more general. The local PCA-based damage detection method is applied for the structural health monitoring of a real bridge using vibration data measured in situ over a one-year period. 2005 Elsevier Ltd. All rights reserved.
A.-M. Yan, G. Kerschen, P. De Boe, J.-C. Golinval, Structural damage diagnosis under changing environmental conditions - Part I: linear analysis, Mechanical Systems and Signal Processing, 2003, submitted for publication.
J.P. Cusumano, and B.Y. Bai Period-infinity periodic motions, chaos and spatial coherence in a 10-degree-of freedom impact oscillator Chaos and Solitons and Fractals 3 1993 515 535
M.F.A. Azeez, and A.F. Vakakis Proper orthogonal decomposition of a class of vibroimpact oscillations Journal of Sound and Vibration 240 2001 859 889
B.F. Feeny, and R. Kappagantu On the physical interpretation of the proper orthogonal modes in vibrations Journal of Sound and Vibration 211 1998 607 616
V. Lenaerts, G. Kerschen, and J.-C. Golinval Identification of a continuous structures with a geometrical non-linearity, Part II: proper orthogonal decomposition Journal of Sound and vibration 262 2003 907 919
H. Sohn, K. Worden, C.F. Farrar, Novelty detection under changing environmental conditions, SPIE's Eigth Annual International Symposium on Smart Structures and Materials, Newport Beach, CA (LA-UR-01-1894), 2001.
M.A. Kramer Nonlinear principal component analysis using autoassociative neural networks AIChE Journal 37 2 1991 233 243
N. Kambhatla, and T.K. Leen Dimension reduction by local PCA Neural Computation 9 1997 1 17
T. Hastie, and W. Stuetzle Principal curves Journal of the American Statistical Association 84 1989 502 516
G. Kerschen, and J.-C. Golinval Non-linear generalization of principal component analysis: from a global to a local approach Journal of Sound and Vibration 254 5 2002 867 876
A. Gersho, and R.M. Gray Vector Quatization and Signal Compression 1992 Kluwer Academic Publishers Norwell
C. Kramer, C.A.M. De Smet, G. De Roeck, Z24-bridge damage detection tests, Proceedings of IMAC 17, Kissimmee, FL, USA February 1999, pp. 1023-1029.
B. Peeters, G. De Roeck, One year monitoring of the Z24-bridge: environmental influences versus damage events, Proceedings of IMAC 18, the International Modal Analysis Conference, San Antonio, TX, USA, February 2000, pp. 1570-1576.
B. Peeters, J. Maeck, G. De Roeck, Dynamic monitoring of the Z24-Bridge: separating temperature effects from damage, Proceedings of the European COST F3 Conference on System Identification and Structural Health Monitoring, Madrid, Spain, June 2000, pp. 377-386.
B. Peeters, System identification and damage detection in civil engineering. Ph.D. Thesis, Katholieke Universiteit Leuven, 2000.
A.M. Yan, J.C. Golinval, B. Peeters, G. De Roeck, A comparative study on damage detection of Z24-Bridge: one-year monitoring with varying environmental conditions, Proceedings of Second E.W. on Structural Health Monitoring 2004, July 7-9, 2004, Munich, Germany, pp. 791-799.
