Journal
SMART MATERIALS AND STRUCTURES
Volume 26, Issue 4, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1361-665X/aa5d41
Keywords
fault identification; piezoelectric impedance/admittance; sensitivity; pre-screening; Bayesian inference; uncertainty
Funding
- Air Force Office of Scientific Research [FA9550-14-1-0384]
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While piezoelectric impedance/admittance measurements have been used for fault detection and identification, the actual identification of fault location and severity remains to be a challenging topic. On one hand, the approach that uses these measurements entertains high detection sensitivity owing to the high-frequency actuation/sensing nature. On the other hand, high-frequency analysis requires high dimensionality in the model and the subsequent inverse analysis contains a very large number of unknowns which often renders the identification problem under-determined. A new fault identification algorithm is developed in this research for piezoelectric impedance/admittance based measurement. Taking advantage of the algebraic relation between the sensitivity matrix and the admittance change measurement, we devise a pre-screening scheme that can rank the likelihoods of fault locations with estimated fault severity levels, which drastically reduces the fault parameter space. A Bayesian inference approach is then incorporated to pinpoint the fault location and severity with high computational efficiency. The proposed approach is examined and validated through case studies.
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