Fault classification method based on DBN model and waveform characteristics for overhead transmission line
Accurate fault identification is highly important to the fault diagnosis of overhead transmission lines (OTLs).In order to improve the efficiency and accuracy of fault identification, the paper proposed a fault identification method based on the deep belief network (DBN) model and the waveform characteristics.Based on the characteristics of different OTL faults,the appropriate characteristic parameters of fault waveform are selected as the input of DBN model, and the fault-cause labels are selected as the output.The effect of DBN model was verified by field data.The results show that the model helps to characterize the relationship between waveform characteristics and fault types, and the proposed method can effectively identify different fault causes in OTLs.
Fault classification DBN Traveling wave Fault detection Transmission line Waveform characteristics
Hanqing Liang Yingjie Yan Yaocheng Li Ying Du Siheng Xiong Yadong Liu
Shanghai Jiao Tong University, No.800 Dongchuan Street, Shanghai 200240, P.R.China
国际会议
法国巴黎
英文
92-97
2019-03-13（万方平台首次上网日期，不代表论文的发表时间）