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Operational Modal Parameter Identification Based on Covariance-Driven Continuous Wavelet Transform and Singular Value Decomposition
The covariance-driven continuous wavelet transform incorporated with singular value decomposition is proposed in the paper to identify the operational modal parameters of structures. The covariance of operational measurements is converted into the time-scale domain using a continuous wavelet transform. Then, by performing singular value decomposition (SVD) on the covariance matrix of multi-measurements, the ridges of the covariance wavelet coefficient are decomposed. The obtained wavelet ridges of the covariance wavelet coefficient that represent the structural modal features are used to estimate the operational natural frequencies and damping ratios. The ratio of cross-covariance wavelet coefficients to auto-covariance wavelet coefficients is proposed to estimate mode shapes. A numerically simulated frame structure and a full-size bridge tested in the field under operational conditions are studied to verify the proposed technique and to demonstrate its accuracy. It has been shown that the proposed technique is reliable and efficient to identify the dynamic characteristics of full-size structures under operational conditions, especially the damping ratios and mode shapes. It has been shown that the proposed covariance-driven continuous wavelet transform method is capable of identifying the dynamic characteristics of full-size structures under operational conditions.
Operational Modal Parameter Identification Based on Covariance-Driven Continuous Wavelet Transform and Singular Value Decomposition
The covariance-driven continuous wavelet transform incorporated with singular value decomposition is proposed in the paper to identify the operational modal parameters of structures. The covariance of operational measurements is converted into the time-scale domain using a continuous wavelet transform. Then, by performing singular value decomposition (SVD) on the covariance matrix of multi-measurements, the ridges of the covariance wavelet coefficient are decomposed. The obtained wavelet ridges of the covariance wavelet coefficient that represent the structural modal features are used to estimate the operational natural frequencies and damping ratios. The ratio of cross-covariance wavelet coefficients to auto-covariance wavelet coefficients is proposed to estimate mode shapes. A numerically simulated frame structure and a full-size bridge tested in the field under operational conditions are studied to verify the proposed technique and to demonstrate its accuracy. It has been shown that the proposed technique is reliable and efficient to identify the dynamic characteristics of full-size structures under operational conditions, especially the damping ratios and mode shapes. It has been shown that the proposed covariance-driven continuous wavelet transform method is capable of identifying the dynamic characteristics of full-size structures under operational conditions.
Operational Modal Parameter Identification Based on Covariance-Driven Continuous Wavelet Transform and Singular Value Decomposition
Ren, Wei-Xin (author) / Xu, Xiao-Xia (author) / Yan, Wang-Ji (author)
Advances in Structural Engineering ; 16 ; 579-591
2013-03-01
13 pages
Article (Journal)
Electronic Resource
English
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