Research on fault diagnosis of power transformer based on classification decision tree algorithm
Wang Tao1, Sun Zhipeng2, Cui Qing1, Zhang Zhilei1, Zhang Tianwei3
1. Hebei Electric Power Company Shijiazhuang Power Supply Company, Shijiazhuang 050051; 2. College of Electrical Engineering, Northeast Electric Power University, Jilin, Jilin 132012; 3. Beijing Runwei Tianhua Power Technology Co., Ltd, Beijing 102211
Abstract：Power transformers are the most important power equipment in the stable operation of power systems. Fault identification of power transformers has always been a top priority for all power work. In recent years, with the development of artificial intelligence, many intelligent algorithms have been introduced into the research of power transformer faults. In this paper, a power tree fault diagnosis model based on decision tree algorithm is proposed. Compared with other classification models, this model has the advantages of high classification accuracy, fast calculation speed, no need for any domain knowledge and parameter assumptions, and easy implementation etc.
王涛, 孙志鹏, 崔青, 张志磊, 张天伟. 基于分类决策树算法的电力变压器故障诊断研究[J]. 电气技术, 2019, 20(11): 16-19.
Wang Tao, Sun Zhipeng, Cui Qing, Zhang Zhilei, Zhang Tianwei. Research on fault diagnosis of power transformer based on classification decision tree algorithm. Electrical Engineering, 2019, 20(11): 16-19.
2019, Vol. 20 
