Decomposition Characteristics of SF 6 and Partial Discharge Recognition under Negative DC Conditions

Ju Tang, Xu Yang, Gaoxiang Ye, Qiang Yao, Yulong Miao and Fuping Zeng
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Ju Tang: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Xu Yang: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Gaoxiang Ye: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Qiang Yao: Chongqing Electric Power Research Institute, Chongqing Power Company, Chongqing 401123, China
Yulong Miao: Chongqing Electric Power Research Institute, Chongqing Power Company, Chongqing 401123, China
Fuping Zeng: School of Electrical Engineering, Wuhan University, Wuhan 430072, China

Energies, 2017, vol. 10, issue 4, 1-16

Abstract: Four typical types of artificial defects are designed in conducting the decomposition experiments of SF 6 gas to obtain and understand the decomposition characteristics of SF 6 gas-insulated medium under different types of negative DC partial discharge (DC-PD), and use the obtained decomposition characteristics of SF 6 in diagnosing the type and severity of insulation fault in DC SF 6 gas-insulated equipment. Experimental results show that the negative DC partial discharges caused by the four defects decompose the SF 6 gas and generate five stable decomposed components, namely, CF 4 , CO 2 , SO 2 F 2 , SOF 2 , and SO 2 . The concentration, effective formation rate, and concentration ratio of SF 6 decomposed components can be associated with the PD types. Furthermore, back propagation neural network algorithm is used to recognize the PD types. The recognition results show that compared with the concentrations of SF 6 decomposed components, their concentration ratios are more suitable as the characteristic quantities for PD recognition, and using those concentration ratios in recognizing the PD types can obtain a good effect.

Keywords: SF6; negative DC-PD; decomposed components; concentration ratio; back propagation neural network; PD recognition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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