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.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.12
- 수록면
- 9 - 19 (11page)
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초록· 키워드
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This paper presents the development of a fault diagnosis and remote data acquisition system for hydraulic solenoid valves designed to enhance machine reliability and serve as a backbone for prognostics and health management (PHM). This system integrates three key technologies. First, an embedded controller utilizing artificial intelligence (AI) detects valve failures by analyzing coil current and voltage signals. Second, an IoT edge device based on a Raspberry Pi with LTE and CAN modules, interfaces with the controller via CAN communication and transmits diagnostic data to a remote server through LTE. Third, a remote server manages and visualizes collected data in real-time, providing valuable insights and analytics. The integration of these technologies was tested in an experimental setup using actual hydraulic solenoid valves. Results demonstrated that the system could promptly detect faults and reliably transmit diagnosis data to the remote server, where accumulated data could be utilized as training data for the diagnostic model, thereby improving its accuracy.
목차
Abstract
1. 서론
2. 밸브 고장 진단 모듈 개발
3. 데이터 원격전송 모듈 개발
4. 진단데이터 관리 서버 구축
5. 시스템 통합 실험
6. 결론
References
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