首页|Novel method for identifying the stages of discharge underwater based on impedance change characteristic
Novel method for identifying the stages of discharge underwater based on impedance change characteristic
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It is difficult to determine the discharge stages in a fixed time of repetitive discharge underwater due to the arc formation process being susceptible to external environmental influences.This paper proposes a novel underwater discharge stage identification method based on the Strong Tracking Filter(STF)and impedance change characteristics.The time-varying equivalent circuit model of the discharge underwater is established based on the plasma theory analysis of the impedance change characteristics and mechanism of the discharge process.The STF is used to reduce the randomness of the impedance of repeated discharges underwater,and then the universal identification resistance data is obtained.Based on the resistance variation characteristics of the discriminating resistance of the pre-breakdown,main,and oscillatory discharge stages,the threshold values for determining the discharge stage are obtained.These include the threshold values for the resistance variation rate(K)and the moment(t).Experimental and error analysis results demonstrate the efficacy of this innovative method in discharge stage determination,with a maximum mean square deviation of Scr less than 1.761.
Department of New Energy,China University of Petroleum,Qingdao 266580,People's Republic of China
Shanghai Ruida Fengzhi Science and Technology Corporation,Shanghai 201703,People's Republic of China
China National Petroleum Group General Research Institute of Engineering and Technology Corporation,Beijing 100029,People's Republic of China
Oil and Gas Resource Survey Center,China Geological Survey,Beijing 100083,People's Republic of China
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shale gas resource evaluation methods and exploration technology research project of the National Science and Technology MajGraduate Innovative Engineering Funding Project of China University of Petroleum(East China)
NETL
NSTL
万方数据
