The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Thermal Change Prediction of Magnetic Switch Using Regression Analysis

회귀 분석 기법을 활용한 전자 개폐기의 온도 변화예측

  • 문철한 (한국기술교육대학교 컴퓨터공학과) ;
  • 연영모 ((주)메티스 연구소) ;
  • 김승희 (한국기술교육대학교 IT융합소프트웨어공학과) ;
  • 민준기 (한국기술교육대학교 컴퓨터공학과)
  • Received : 2022.09.27
  • Accepted : 2022.11.01
  • Published : 2022.11.30
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Abstract

Electricity is essential energy in modern society, such as being used in various industries. However, the rate of fires occurring on electric wiring to deal with it is very high. In this work, we implemented a system to predict the temperature change of an electric circuit through analysis using various regression models. To do so, we collected the temperature data of 27 types of magnetic switches which control electric circuits as well as trained the regression models by using the collected temperature data. In our experiments, we confirmed that the regression models can be trained at a sufficiently usable level since the difference between the actual temperature and predicted temperature is about 4℃. The results of our work will be useful to predict the temperature of electric circuits and preventing fires on them.

전기는 다양한 산업에 이용되는 등 현대 사회에 있어서 필수적인 에너지이다. 그러나, 이를 다루기 위한 전자배선 상에서 발생하는 화재의 비율이 매우 높다. 본 연구에서는 다양한 회귀 모델들을 사용한 분석을 통하여 전기 회로의 온도 변화를 예측하는 시스템을 구현하였다. 이를 위해 전기 회로를 제어하는 전자 접촉기 27종을 사용한 회로상의 온도 데이터를 수집하고 수집된 온도 데이터를 이용하여 회귀 모델들을 훈련하였다. 실험에서 실제 온도와 예측온도의 차이가 평균 4℃ 정도 발생하여, 이를 통해 충분히 사용 가능한 수준의 모델을 훈련할 수 있음을 확인하였다. 이와 같은 연구 결과는 전기 회로의 온도 예측 및 화재 예방에 도움이 될 것이다.

Keywords

Acknowledgement

이 논문은 2022년도 한국기술교육대학교 교수 교육연구진흥과제 지원에 의하여 연구되었음.

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