Title: Advanced Condition-Based Maintenance of Composites Based on Real-Time Electromechanical Behavior Data

Authors: In-Yong Lee, Soyoung Oh and Young-Bin Park

DOI: 10.33599/nasampe/c.22.0105

Abstract: Studies on real-time structural health monitoring (SHM) and prognostics and health management (PHM) for composite structures using self-sensing data are limited. For reducing the unexpected failure, maintenance cost and maximize the life cycle of composites structures, study for CBM+ which is consisted with SHM and PHM is needed. This study proposes an advanced real-time condition-based maintenance methodology for composites under cyclic stress condition based on their electromechanical behavior. The electrical resistance of carbon fiber composite structures is measured under cyclic stress condition such as repeated impacts test. The electromechanical behavior is investigated, and the various damage types in the composite structures are analyzed during multiple impacts testing using designed data analysis system by comparing the electromechanical behavior with material property. PHM algorithms are proposed in this study to predict the electromechanical behavior of a composite during cyclic test using the particle filter. Furthermore, remaining useful property was calculated in real-time with few number of historical data. Based on SHM and PHM analysis, this study introduces a real-time condition-based maintenance methodology for efficient system maintenance by combining SHM and PHM, using real-time self-sensing data. The applicability of the method was verified by using it to assess the impact damage on wind turbine blade.

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Conference: CAMX 2022

Publication Date: 2022/10/17

SKU: TP22-0000000105

Pages: 11

Price: $22.00