Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 26, Issue -, Pages 91-103Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2011.07.005
Keywords
Time-varying system; Wavelet; State-space; Identification; Scaling function; Orthogonality
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Funding
- National Natural Science Foundation of China [10772076, 11172131]
- innovative project for postgraduate education of Jiang Su Province [CX10B_088Z, CX09B_071Z]
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In this paper a new wavelet-based state-space method for the identification of dynamic parameters in linear time-varying systems is presented using free vibration response data and forced vibration response data. For an arbitrarily linear time-varying system, the second-order vibration differential equations are first rewritten as the first-order state equations using the state-space theory. The excitation and response signals are projected using the Daubechies wavelet scaling functions and the first-order state-space equations are transformed into simple linear equations using the orthogonality of the scaling functions. This allows the time-varying equivalent state-space system matrices at each moment to be identified directly via solving the linear equations. The system modal parameters are extracted though eigenvalue decomposition of the state-space system matrices. The stiffness and damping matrices are determined by comparing the identified equivalent system matrices with the physical system matrices. The proposed algorithm is investigated with a two-degree of freedom spring-mass-damper system and a cantilever beam. Numerical results demonstrate that the proposed method is robust and effective with regards to the identification of abruptly, smoothly and periodically time-varying parameters. (C) 2011 Elsevier Ltd. All rights reserved.
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