Bowen Yu, Chunli Xie*
CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1329-1343, 2024, DOI:10.32604/cmc.2023.046248
Abstract With the advent of Industry 4.0, marked by a surge in intelligent manufacturing, advanced sensors embedded in smart factories now enable extensive data collection on equipment operation. The analysis of such data is pivotal for ensuring production safety, a critical factor in monitoring the health status of manufacturing apparatus. Conventional defect detection techniques, typically limited to specific scenarios, often require manual feature extraction, leading to inefficiencies and limited versatility in the overall process. Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes. Our proposed approach encompasses a suite… More >
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