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The continuous wavelet transform as a stochastic process for damage detection

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

This paper presents the formulation of a novel statistical model for the wavelet transform of the acceleration response of a structure based on Gaussian Process Theory. The model requires no prior knowledge of the structural properties and all the model parameters are learned directly from the measured data using Maximum Likelihood Estimation. The proposed model is applied to the data obtained from a series of shake table tests and the results are presented. The results, even at a proof-of-concept level, appear to correlate well with the ocurrence of damage, which is an indication of the validity of the underlying model. The results from the use of a simple metric for the detection of damage are presented as well.

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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076122

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/