| Title |
Development of a Deep Learning-Based Deterioration Diagnosis System in Switchgear |
| Authors |
강태형(Tae-Hyung Kang) ; 방준호(Jun-Ho Bang) ; 유인호(In-Ho Ryu) |
| DOI |
https://doi.org/10.5370/KIEE.2024.73.9.1588 |
| Keywords |
Deep Learning; Object Detection; Deterioration Diagnosis; Status Diagnosis; Switchgear |
| Abstract |
The switchgear is a device which receives the high voltage electricity from the generator it into the useable voltage for the consumers. It is an infrastructure can provide the useable voltage from the households to the big facilities throughout our society.
But If a blackout emergency occurs, it can cause serious damage. Altuogh the regular inspection of the switchgear is required to prevent the problems and for the safe maintenance, it is very hard because of some factors like non-standardized equipments, dangerous and narrow working spaces and so on. In this paper, we are about to talk about possibility of adapting the thermal imaging camera for the safer and more effecient monitoring and surveillance. We have developed a deep learning-based thermal diagnostic system which can check the information of the main equipments. It also can detect the status data varying by the temperature and notify an alarm to the manager. |