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Particle filters for structural system identification using multiple test and sensor data: A combined computational and experimental study

Nasrellah, HA and Manohar, CS (2011) Particle filters for structural system identification using multiple test and sensor data: A combined computational and experimental study. In: Structural Control and Health Monitoring, 18 (1). pp. 99-120.

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Official URL: http://onlinelibrary.wiley.com/doi/10.1002/stc.361...

Abstract

The problem of structural system identification when measurements originate from multiple tests and multiple sensors is considered. An offline solution to this problem using bootstrap particle filtering is proposed. The central idea of the proposed method is the introduction of a dummy independent variable that allows for simultaneous assimilation of multiple measurements in a sequential manner. The method can treat linear/nonlinear structural models and allows for measurements on strains and displacements under static/dynamic loads. Illustrative examples consider measurement data from numerical models and also from laboratory experiments. The results from the proposed method are compared with those from a Kalman filter-based approach and the superior performance of the proposed method is demonstrated. Copyright (C) 2009 John Wiley & Sons, Ltd.

Item Type: Journal Article
Additional Information: Copyright of this article belongs to John Wiley and Sons.
Keywords: structural system identification; particle filters; dynamic state estimation
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 29 Mar 2011 11:51
Last Modified: 29 Mar 2011 11:51
URI: http://eprints.iisc.ernet.in/id/eprint/36332

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