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
- 학위논문
- 저자정보
- 발행연도
- 2020
- 저작권
- 순천대학교 논문은 저작권에 의해 보호받습니다.
이용수25
이 논문의 연구 히스토리 (3)
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초록· 키워드
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Rapid national development of the utility industry has emphasized the importance of electrical safety. The cost incurred by electrical accidents have increased enormously, including human and financial loss.
Portable infrared thermography cameras are widely used to inspect poor electrical equipments by sensing its temperature. However, it is difficult to determine electrical equipment failures by temperature only. Inspector’s knowledge and real-time monitoring are necessary for a reliable diagnosis.
This paper presents a diagnostic system that predicts the facilities failure in real time by monitoring the temperature and the electrical data of a power system. The system consists of a micro processor module and a PC server. The micro processor module contains a processor that collects the electrical data and an infrared camera that collects temperature image data. The PC server then stores the collected data. With the collected data, a prediction algorithm is formed to forecast facility failures.
The prediction algorithm is based on a mathematical model designed by the correlation between collected temperature data and electrical data. The failure of the facilities is determined by the difference between the value measured from the equipment and the expected value calculated by the mathematical model.
To test the prediction algorithm, test beds are made using switchboards and electrical load simulating a facility failed state. Utilizing these test beds, the developed prediction algorithm was verified.
Portable infrared thermography cameras are widely used to inspect poor electrical equipments by sensing its temperature. However, it is difficult to determine electrical equipment failures by temperature only. Inspector’s knowledge and real-time monitoring are necessary for a reliable diagnosis.
This paper presents a diagnostic system that predicts the facilities failure in real time by monitoring the temperature and the electrical data of a power system. The system consists of a micro processor module and a PC server. The micro processor module contains a processor that collects the electrical data and an infrared camera that collects temperature image data. The PC server then stores the collected data. With the collected data, a prediction algorithm is formed to forecast facility failures.
The prediction algorithm is based on a mathematical model designed by the correlation between collected temperature data and electrical data. The failure of the facilities is determined by the difference between the value measured from the equipment and the expected value calculated by the mathematical model.
To test the prediction algorithm, test beds are made using switchboards and electrical load simulating a facility failed state. Utilizing these test beds, the developed prediction algorithm was verified.
목차
제 1 장 서 론 11.1 연구배경 및 필요성 11.2 연구의 동향 41.3 연구의 목적 및 내용 6제 2 장 전기설비의 열적 특성 72.1 적외선 특성 72.2 전기설비의 열 이론 152.3 전력과 온도의 상관계수 분석 방법 202.4 열화상 장비를 활용한 전기설비의 진단 방법 22제 3 장 적외선 열화상 시스템 개발 253.1 시스템의 구성 253.2 전류와 온도의 실험 특성 41제 4 장 실험결과 및 분석 494.1 정상상태 분석 및 기준 설정 504.2 고장상태 분석 및 기준 설정 524.3 알고리즘 기준 설정 544.4 고장 상태 분석 및 검증 55제 5 장 결 론 57
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