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Proceedings Paper

Ambient data analysis for robust and efficient structural identification
Author(s): Jian Zhang; Franklin Moon; Ahmet Aktan
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Paper Abstract

Various uncertainties involved in the structural modeling and experiment processes greatly limit the application of the system identification (St-Id) technology on the real-life structural health monitoring and risk-based decision making. An efficient St-Id method is proposed to accurately identify structural modal parameters by using ambient test data with various uncertainties. The random decrement technique is first applied to reduce random errors by averaging the test data. Subsequently, a high order Vector Backward Auto-Regressive (VBAR) model is proposed to identify structural modal parameters. The merit of the VBAR model is that it awards a determine way to separate the system modes consisting of structural parameters and the extraneous modes arising due to uncertainties. The ambient vibration data from a cantilever beam experiment is employed to demonstrate the effectiveness of the proposed St-Id method.

Paper Details

Date Published: 30 March 2009
PDF: 9 pages
Proc. SPIE 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009, 729237 (30 March 2009); doi: 10.1117/12.816123
Show Author Affiliations
Jian Zhang, Drexel Univ. (United States)
Franklin Moon, Drexel Univ. (United States)
Ahmet Aktan, Drexel Univ. (United States)

Published in SPIE Proceedings Vol. 7292:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009
Masayoshi Tomizuka, Editor(s)

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