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김선원(Seon-Won Kim),안강현(Kanghyeon An),백지선(Jiseon Back),이상권(Sang-Kwon Lee),이창호(Changho Lee),김풍길(Pungil Kim) 한국소음진동공학회 2021 한국소음진동공학회 논문집 Vol.31 No.1
The power driving system (PDS) comprises parts such as the chain, sprocket, gear, bearing, and rotating shaft. The purpose of this study is to develop a condition-monitoring device that diagnoses component defects early by using a convolutional neural network to prevent complete damage due to component defects. For this study, eight types of defects are artificially manufactured in various parts and assembled to build a PDS. A convolutional neural network is developed to classify and diagnose the eight types of defects. A feature for faults is successfully extracted, and fault classification is achieved with 90 % accuracy.