Compressed Change Detection For Structural Health Monitoring

Abstract

The problem of detection of a sparse number of damages in a structure is considered. The idea relies on the newly developed framework for compressed change detection [1], which leverages the unique covering property of identifying codes to detect statistical changes in stochastic phenomena. Since only a small number of damage scenarios can occur simultaneously, change detection is applied to responses of pairs of sensors that form an identifying code over a learned damage-sensing graph. An asymptotic analysis of the detection delay and the probability of detection of the proposed approach is provided when the number of damage scenarios is large.

Publication Date

4-24-2015

Publication Title

Conference Record - Asilomar Conference on Signals, Systems and Computers

Volume

2015-April

Number of Pages

1231-1235

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ACSSC.2014.7094655

Socpus ID

84940560176 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84940560176

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