System parameter identification from projection of inverse analysis

Publication Type:
Journal Article
Citation:
Journal of Sound and Vibration, 2017, 396 pp. 83 - 107
Issue Date:
2017-05-26
Metrics:
Full metadata record
Files in This Item:
Filename Description Size
System parameter ID from projection of inverse analysis.pdfPublished Version3.45 MB
Adobe PDF
© 2017 Elsevier Ltd The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.
Please use this identifier to cite or link to this item: