인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Purpose: To establish a condition-based maintenance plus (CBM+) and prognostics and health management (PHM) methodology using normal vibration signals in the development of weapon systems.
Methods: A fault probability-based health index using physical features associated with shaft and bearing failure to perform anomaly detection and fault diagnosis.
Results: The methodology was verified using shaft crack test data and bearing acceleration life test data. In shaft crack test data, the shaft health index increased more than the bearing health index. By contrast, in bearing acceleration life test data, the bearing health index increased more than the shaft health index.
Conclusion: This study on designing a normal vibration signal-based anomaly detection and fault diagnosis methodology is expected to broaden the application of CBM+ and PHM in weapon systems.
Methods: A fault probability-based health index using physical features associated with shaft and bearing failure to perform anomaly detection and fault diagnosis.
Results: The methodology was verified using shaft crack test data and bearing acceleration life test data. In shaft crack test data, the shaft health index increased more than the bearing health index. By contrast, in bearing acceleration life test data, the bearing health index increased more than the shaft health index.
Conclusion: This study on designing a normal vibration signal-based anomaly detection and fault diagnosis methodology is expected to broaden the application of CBM+ and PHM in weapon systems.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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