인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
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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
Abstract The aim of the work was to trace the relationship between the durability of the equipment and its maintenance strategy. This is done by examples of basic structures of industrial equipment. They have a long service life and during this time manage to accumulate certain damages that need to be diagnosed, after which decisions on its maintenance and repair must be made. Problems associated with the technique for extending the service life of industrial equipment are addressed. The authors have created a technique called the resource safety index (RSI), which uses this characteristic as a diagnostic metric. The usage of the risk function to control the technical state of base structures is shown in this study. It is demonstrated how the behavior of the risk function affects the choice of the inspection model. A risk function model for base structures is proposed, which is based on the concepts of stepwise assignment of the limit state and the corresponding useful life. An algorithm for determining the optimal period of restoration measures according to minimizing the cost intensity criterion, where the risk indicator is a parameter, has been developed. The proposed concepts were put into practice when deciding on the further operation of the housings of the 350 pipes rolling unit. The housings of the piercing mill and the automatic mill, which had been in operation for 80 years, were diagnosed. For the first time, it was discovered that the housings risk function at the crack break through point stage can be represented by a linear dependence directly proportional to the accumulation of operating time. One of the signs of deterioration in the technical condition of rolling mill stands is a malfunction of the system of fixing and securing the housings.
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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