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.
피인용 0
초록·키워드
The purpose of this paper is to propose a strategy for assigning condition codes in the health indexing of GIS (Gas-Insulated Switchgear), a critical component in ensuring the reliable operation of power systems. Traditional asset management strategies, which rely on estimated lifespans, often lead to inefficiencies, especially in determining the optimal timing for maintenance or replacement. To overcome these challenges, CBRM (Condition-Based Risk Management) has gained prominence as a solution, using health and criticality indices to optimize decisions based on the actual condition of assets. This study aims to develop a health indexing framework for GIS that accurately reflects the condition of its components and subsystems. The proposed framework introduces a structured methodology for assigning condition codes by combining a logarithmic scale with ‘summation’ and ‘worst case’ computation, computation. This effectively reduces the masking effect that is often encountered in approaches that combine a linear scale with weighted summation. Additionally, a combination of worst case and summation approaches is used in calculating condition codes to ensure that the condition of each component is appropriately represented in the overall health index of the GIS. By addressing the probability of failure based on actual conditions, this framework allows for timely interventions and enhances the operational efficiency of assets. Ultimately, the proposed strategy contributes to the long-term reliability of power infrastructure and offers valuable insights for improving risk management practices.
본문·목차
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