딥러닝 기반 무인전력설비 감시시스템 개발을 위한 학습 데이터 셋 구축 연구

Abstract

Since the emergence of deep learning technology, research and development using it in various industries has been in progress. In the power field, deep learning technology based on image recognition has been in the spotlight for the development of condition diagnosis and monitoring systems. However, in order to increase the performance of the deep learning model, it is necessary to build a large data set for learning it as well as the deep learning model. Therefore, in this paper, we propose a dataset creation method for development of unmanned power facility monitoring system based on deep learning. In an environment in which a PTZ camera and a 360-degree camera are operated simultaneously, various method for generating learning data were proposed, and the performance of the learning data set was proved through the detection system experiment.