Lecturer, Alzaiem Alzhari University, Khartoum, Sudan.
Particle filters for structural system identification using multiple test and sensor data: A combined computational and experimental study
Version of Record online: 13 NOV 2009
Copyright © 2010 John Wiley & Sons, Ltd.
Structural Control and Health Monitoring
Volume 18, Issue 1, pages 99–120, February 2011
How to Cite
Nasrellah, H. A. and Manohar, C. S. (2011), Particle filters for structural system identification using multiple test and sensor data: A combined computational and experimental study. Struct. Control Health Monit., 18: 99–120. doi: 10.1002/stc.361
- Issue online: 13 NOV 2009
- Version of Record online: 13 NOV 2009
- Manuscript Accepted: 17 SEP 2009
- Manuscript Revised: 2 AUG 2009
- Manuscript Received: 16 NOV 2008
- structural system identification;
- particle filters;
- dynamic state estimation
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 © 2010 John Wiley & Sons, Ltd.