| Title |
A Study on the Selection of Safety Standards for Uninterruptible Diagnostic Technology for Electrical Equipment and Establishment of a Test-bed |
| Authors |
Jae-Yoon Lee ; Il-Rea Noh ; Il-Moo Lee |
| DOI |
http://doi.org/10.5207/JIEIE.2022.36.6.036 |
| Keywords |
Big data/AI; Institutional improvement; Online status determination; Risk precursor prediction; Uninterruptible diagnosis |
| Abstract |
Electrical safety accidents in multi-use and energy-concentrated facilities accompany any property loss and human casualties being increased in large scale. Therefore, the research on aging diagnosis and replacement/individual work technology is being actively ongoing. Currently, safety diagnosis focusing on power off-line diagnosis can only check the status of insulation and rating of each facility, which is different from the actual operating condition. This paper describes the technical methodologies and implementations such as uninterruptible diagnostic technology, electrical equipment diagnostic data, safety standard selection, and test-bed establishment neccessary for AI live diagnosis system using big data from IoT sensors other than power off-line diagnosis. Based on this, we would like to suggest a guideline for stable power supply and maintenance to apply the preventive diagnosis system for electrical equipment. |