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초록
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.
키워드
Convolutional Neural Network; Continuous wavelet transform; Power Driving System; 합성곱 신경망; 연속 웨이블렛 변환; 동력 구동 시스템
- 제목
- 소음 신호를 이용한 딥러닝 이용파워 드라이빙 시스템의 건전성 감시
- 제목 (타언어)
- Health Monitoring of Power Driving System Using Sound Signalbased on Deep Learning
- 저자
- 김선원; 안강현; 백지선; 이상권; 이창호; 김풍길
- 발행일
- 2021-02
- 유형
- Y
- 저널명
- 한국소음진동공학회논문집
- 권
- 31
- 호
- 1
- 페이지
- 47 ~ 56