DAMAGE SENSING AND SELF-HEALING SYSTEM OF CARBON FIBER REINFORCED POLYMER COMPOSITES USING DEEP-LEARNING

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초록

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

addressable conducting networkCarbon fiber reinforced polymer compositedamage sensingdeep-learningself-healingCarbon fiber reinforced plasticsCompression testingDamage detectionLearning algorithmsNeural networksSelf-healing materialsDeep learningAddressable conducting networkCarbon fiber reinforced polymer compositeConducting networksDamage sensingDamaged areaDeep-learningHigh-accuracySelf-healingSelf-healing systemsSensing systems
제목
DAMAGE SENSING AND SELF-HEALING SYSTEM OF CARBON FIBER REINFORCED POLYMER COMPOSITES USING DEEP-LEARNING
저자
Yu, Myeong-HyeonLee, Ji-SeokKim, Hak Sung
발행일
2022-06
유형
Conference Paper
저널명
ECCM 2022 - Proceedings of the 20th European Conference on Composite Materials: Composites Meet Sustainability
4
페이지
1039 ~ 1045