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Title |
Development of an Impact-Response Technique for Automated Detection and Classification of Backside Defects in Nuclear Containment Liner Plates
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Authors |
강준구(Jungu Kang) ; 김동준(Dongjun Kim) ; 최하진(Hajin Choi) ; 이철우(Cheolwoo Lee) ; 김홍섭(Hongseop Kim) ; 송호민(Homin Song) |
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DOI |
https://doi.org/10.11112/jksmi.2025.29.6.164 |
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Keywords |
격납건물 라이너 플레이트; 배면 결함; 충격-응답; 비파괴 평가; 머신러닝; 결함 시각화 Containment liner plate (CLP); Interface defects; Impact-response; Nondestructive evaluation; Machine learning; Defect visualization |
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Abstract |
This study developed a method to effectively detect and automatically classify major defects that may occur behind the containment liner plate (CLP) of nuclear power plant containments. For this purpose, the impact-response technique was applied by striking the specimen surface and measuring the vibration response using an accelerometer. Analysis of the acquired signals revealed that defect characteristics were not clearly distinguished in the frequency domain, whereas the time-domain signals clearly differentiated not only between sound and defective regions but also among defect types. Accordingly, the time-domain signals were employed as input data for a one-dimensional convolutional neural network (1-D CNN) model, which classified CLP backside defects including voids, kissing bonds, and wall-thinning. The proposed model achieved an accuracy of approximately 98% on the validation dataset and 100% on the test dataset. These results suggest that the proposed approach can complement existing nondestructive evaluation techniques and is expected to contribute to the structural integrity assessment and safety assurance of nuclear power plant containments.
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