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In this research, we report a new fault identification algorithm utilizing multi-objective optimization. Fault identification problem is commonly under-determined, as measurement information may not be sufficient to facilitate a direct inversion. We formulate an optimization problem, aiming at minimizing the discrepancy between model prediction and measurement. This yields multiple possible fault scenarios, which lays down foundation for further inspection.
Yang Zhang andJ. Tang
"Structural damage identification using multi-objective optimization based inverse analysis", Proc. SPIE 11380, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIV, 113800D (21 May 2020); https://doi.org/10.1117/12.2558982
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Yang Zhang, J. Tang, "Structural damage identification using multi-objective optimization based inverse analysis," Proc. SPIE 11380, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIV, 113800D (21 May 2020); https://doi.org/10.1117/12.2558982