Sequential Monte Carlo based prediction of crack propagations in carbon fiber composites using electrical resistance measurement

Inyong Lee; Young-Bin Park; Hyung Doh Roh

doi:10.1117/12.2582961

22 March 2021 Sequential Monte Carlo based prediction of crack propagations in carbon fiber composites using electrical resistance measurement

Inyong Lee, Young-Bin Park, Hyung Doh Roh

Author Affiliations +

Proceedings Volume 11592, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XV; 115921B (2021) https://doi.org/10.1117/12.2582961
Event: SPIE Smart Structures + Nondestructive Evaluation, 2021, Online Only

Conference Poster

Abstract

Health state monitoring and prognostics and management of composite were investigated with piezoresistivity data based on the electromechanical behavior of carbon fibers during dual cantilvever bending testing. Crack length in real-time and remaining crack length were calculated with measured electrical resistance. Prediction of crack length was estimated based on prediction result of electromechanical behavior. This research indicated optimized in situ diagnosis and prognosis of carbon fiber reinforced composites with self-sensing data. Self-sensing capability of self-sensing data using electrical resistance was investigated which is applicable to both SHM and PHM.

Conference Presentation

Citation Download Citation

Inyong Lee, Young-Bin Park, and Hyung Doh Roh "Sequential Monte Carlo based prediction of crack propagations in carbon fiber composites using electrical resistance measurement", Proc. SPIE 11592, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XV, 115921B (22 March 2021); https://doi.org/10.1117/12.2582961

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