TY - GEN
T1 - Structural Damage Identification Using Piezoelectric Impedance Sensing with Enhanced Optimization and Enriched Measurements
AU - Zhang, Yang
AU - Dupont, Joshua
AU - Wang, Ting
AU - Zhou, Kai
AU - Tang, Jiong
N1 - Funding Information:
This research is supported in part by This research is supported in part by a Space Technology Research Institutes grant (number 80NSSC19K1076) from NASA’s Space Technology Research Grants Program and in part by the National Science Foundation under grant CMMI-1825324.
Publisher Copyright:
© 2023 SPIE.
PY - 2023/4
Y1 - 2023/4
N2 - Fault parameters in a structure can be identified by matching measurements with model predictions in the parametric space. As high frequency measurements are preferred to uncover small-size damage, piezoelectric impedance/admittance active interrogation has shown promising aspects. Nevertheless, the amount of useful measurement information is generally insufficient to pinpoint damage, and the inverse identification is underdetermined. In this research, we develop a combinatorial enhancement to tackle these challenges. A tunable piezoelectric impedance sensing procedure is developed in which an adaptive inductance element is integrated with the piezoelectric transducer, which will lead to enriched measurement data for the same damage. Subsequently, an intelligent multi-objective particle swarm optimization approach is synthesized to inversely identify the damage location and severity. Case studies are conducted to highlight the accuracy of the damage identification.
AB - Fault parameters in a structure can be identified by matching measurements with model predictions in the parametric space. As high frequency measurements are preferred to uncover small-size damage, piezoelectric impedance/admittance active interrogation has shown promising aspects. Nevertheless, the amount of useful measurement information is generally insufficient to pinpoint damage, and the inverse identification is underdetermined. In this research, we develop a combinatorial enhancement to tackle these challenges. A tunable piezoelectric impedance sensing procedure is developed in which an adaptive inductance element is integrated with the piezoelectric transducer, which will lead to enriched measurement data for the same damage. Subsequently, an intelligent multi-objective particle swarm optimization approach is synthesized to inversely identify the damage location and severity. Case studies are conducted to highlight the accuracy of the damage identification.
KW - particle swarm optimization
KW - piezoelectric transducer
KW - Structural fault identification
KW - tunable inductor
UR - http://www.scopus.com/inward/record.url?scp=85159962424&partnerID=8YFLogxK
U2 - 10.1117/12.2658628
DO - 10.1117/12.2658628
M3 - Conference article published in proceeding or book
AN - SCOPUS:85159962424
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023
A2 - Su, Zhongqing
A2 - Glisic, Branko
A2 - Limongelli, Maria Pina
PB - SPIE
T2 - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023
Y2 - 13 March 2023 through 16 March 2023
ER -