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Study on Earth Surface Potential and DC Current Distribution around DC Grounding Electrode 被引量:1
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作者 Zhi-chao Ren Chun-yan Ye Hai-yan Wang 《Energy and Power Engineering》 2013年第4期792-796,共5页
DC magnetic biasing problem,caused by the DC grounding electrode, threatened the safe operation of AC power grid. In this paper, the characteristics of the soil stratification near DC grounding electrode was researche... DC magnetic biasing problem,caused by the DC grounding electrode, threatened the safe operation of AC power grid. In this paper, the characteristics of the soil stratification near DC grounding electrode was researched. The AC-DC interconnected large-scale system model under the monopole operation mode was established. The earth surface potential and DC current distribution in various stations under the different surface thickness was calculated. Some useful conclusions are drawn from the analyzed results. 展开更多
关键词 DC GROUNDING ELECTRODE Magnetic BIASING Soil STRATIFICATION Earth Surface Potential DC Current DISTRIBUTION
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Identification of ultra-high-frequency PD signals in gas-insulated switchgear based on moment features considering electromagnetic mode
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作者 Feng Bin Feng Wang +3 位作者 Qiuqin Sun She Chen Jingmin Fan Huisheng Ye 《High Voltage》 SCIE EI 2020年第6期688-696,共9页
The feature extraction and pattern recognition techniques are of great importance to assess the insulation condition of gas-insulated switchgear.In this work,the ultra-high-frequency partial discharge(PD)signals gener... The feature extraction and pattern recognition techniques are of great importance to assess the insulation condition of gas-insulated switchgear.In this work,the ultra-high-frequency partial discharge(PD)signals generated from four types of typical insulation defects are analysed using S-transform,and the greyscale image in time-frequency representation is divided into five regions according to the cutoff frequencies of TEm1 modes.Then,the three low-order moments of every subregion are extracted and the feature selection is performed based on the J criterion.To confirm the effectiveness of selected moment features after considering the electromagnetic modes,the support vector machine,k-nearest neighbour and particle swarm-optimised extreme learning machine(ELM)are utilised to classify the type of PD,and they achieve the recognition accuracies of 92,88.5 and 95%,respectively.In addition,the results show that the ELM offers good generalisation performance at the fastest learning and testing speeds,thus more suitable for a real-time PD detection. 展开更多
关键词 INSULATION MOMENT FEATURES
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