메뉴 건너뛰기
소속 기관 / 학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
고객센터 ENG
주제분류

논문 기본 정보

저자정보
(Electrical Safety Research Institute of KESCO) (Electrical Safety Research Institute of KESCO) (Electrical Safety Research Institute of KESCO) (Electrical Safety Research Institute of KESCO) (Electrical Safety Research Institute of KESCO) (Electrical Safety Research Institute of KESCO) (Korea Electrical Safety Corporation)
저널정보
대한전기학회 전기학회논문지 전기학회논문지 제75권 제3호
오류 신고하기

피인용 0

검색

    초록·키워드

    To overcome these limitations, this study applies three-dimensional X-ray computed tomography (3D X-ray CT) as a non-destructive technique for investigating electrical equipment failures. The CT system reconstructs multiple two-dimensional X-ray projections into a volumetric 3D model, allowing for the visualization and quantitative analysis of internal defects such as voids, cracks, carbonized zones, and melting marks without damaging the specimen. A series of case studies were conducted on various electrical components — including power cables, straight joint splices, printed circuit boards (PCB), and vacuum circuit breakers (VCB). The results demonstrate that 3D X-ray CT enables clear identification of short-circuit-induced melting zones, insulation breakdown paths, and contact degradation areas that were previously unobservable by conventional methods. In particular, it allowed the determination of current flow direction, heat concentration patterns, and the progression of partial discharge-related damage in three dimensions. These findings highlight the effectiveness of 3D X-ray CT as a forensic and diagnostic tool in electrical safety engineering. Beyond post-accident analysis, the technique offers potential for predictive diagnostics and condition-based maintenance by providing reproducible, quantitative data on internal degradation. This study contributes to the advancement of scientific, standardized approaches to electrical failure investigation and establishes a foundation for integrating CT-based data analysis with artificial intelligence to enhance automation and objectivity in future safety diagnostics.

    최근 본 자료 전체보기

      UCI(KEPA) : I410-151-26-02-096345278