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Proceedings Paper

Dynamic shape estimation using Kalman filtering
Author(s): Peter S. Lively; Mauro J. Atalla; Nesbitt W. Hagood
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Paper Abstract

This paper proposes the use of a modern control method, the Kalman filter, to perform dynamic shape estimation of structures. Existing dynamic shape estimation techniques use static estimation techniques at each time step. This approach has been shown to be unsatisfactory, since aliasing of the higher modes, which is largely not seen in the static case, occurs strongly in the dynamic case. In many cases the aliasing produces signal to noise ratios significantly greater than unity. The proposed approach uses a Kalman filter to sift out the desired low frequency modes, since they contribute the most to the displacements, and treats the higher modes as a component of the noise in the system. Also, unlike the static techniques, the Kalman filter allows sensing of a number of modes larger than the number of sensors, and it takes into account the measurement errors. Numerical simulations show that the Kalman filtering technique can reduce the error from a thousand percent down to less than a percent for an ideal cantilever beam. Experimental data, susceptible to modeling and sensing errors, show that the proposed method results in a significant improvement over existing techniques.

Paper Details

Date Published: 22 June 2000
PDF: 12 pages
Proc. SPIE 3985, Smart Structures and Materials 2000: Smart Structures and Integrated Systems, (22 June 2000); doi: 10.1117/12.388854
Show Author Affiliations
Peter S. Lively, Massachusetts Institute of Technology (United States)
Mauro J. Atalla, Massachusetts Institute of Technology (United States)
Nesbitt W. Hagood, Massachusetts Institute of Technology (United States)


Published in SPIE Proceedings Vol. 3985:
Smart Structures and Materials 2000: Smart Structures and Integrated Systems
Norman M. Wereley, Editor(s)

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