| Title |
Study of Technique and Case Studies of Electrical Equipment Failures Based on 3D X-ray CT |
| Authors |
김정기(Jeong-Gi Kim) ; 이진식(Jin-Sik Lee) ; 김재현(Jae-Hyun Kim) ; 김정환(Jeong-Hwan Kim) ; 최치우(Chi-Woo Choi) ; 전정채(Jeong-Chay Jeon) ; 김용혁(Yong-Hyeok Kim) |
| DOI |
https://doi.org/10.5370/KIEE.2026.75.3.637 |
| Keywords |
Electric Disaster; Xray; X-ray; 3D CT X-ray; Electrical Installation Fault; Electrical Fire cause identification |
| Abstract |
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. |