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DAMAGE SENSING AND SELF-HEALING SYSTEM OF CARBON FIBER REINFORCED POLYMER COMPOSITES USING DEEP-LEARNING
- Yu, Myeong-Hyeon;
- Lee, Ji-Seok;
- Kim, Hak Sung
SCOPUS
0초록
In this work, damage sensing and self-healing of carbon fiber reinforced polymer composite (CFRP) was conducted based on an addressable conducting network (ACN). For the high accuracy of damage sensing, a deep-learning based damage sensing system was developed. The training data was generated through Kirchhoff's circuits laws. Then, the Artificial Neural Network (ANN) based deep learning algorithm was used for damage sensing. In addition, selfhealing of the detected damage was performed. The self-healing was conducted by supplying an electric current to the damaged area. Supplied electric current generates joule heat in the damaged area. As a result, it was noteworthy that established deep-learning algorithm based on ACN exhibited high accuracy damage sensing resolution under compression test. In addition, the self-healing for damaged CFRP panels was also successfully performed.
키워드
- 제목
- DAMAGE SENSING AND SELF-HEALING SYSTEM OF CARBON FIBER REINFORCED POLYMER COMPOSITES USING DEEP-LEARNING
- 저자
- Yu, Myeong-Hyeon; Lee, Ji-Seok; Kim, Hak Sung
- 발행일
- 2022-06
- 유형
- Conference Paper
- 저널명
- ECCM 2022 - Proceedings of the 20th European Conference on Composite Materials: Composites Meet Sustainability
- 권
- 4
- 페이지
- 1039 ~ 1045