王立宪,马宏忠,戴 锋.基于机电联合的 GIL 局部放电趋势预测研究[J].电子测量与仪器学报,2021,35(10):98-106
基于机电联合的 GIL 局部放电趋势预测研究
Research on partial discharge trend prediction of GIL based on WOA-ELM
  
DOI:
中文关键词:  GIL  局部放电  振动信号  鲸鱼优化算法  极限学习机
英文关键词:GIL  partial discharge  vibration signal  WOA  ELM
基金项目:中国博士后科学基金(2020M671318)、江苏省自然科学基金青年基金(BK20190490)、国网江苏省电力公司重点科技项目(J2020040)资助
作者单位
王立宪 1. 河海大学 能源与电气学院 
马宏忠 1. 河海大学 能源与电气学院 
戴 锋 2. 国网江苏省电力有限公司检修分公司 
AuthorInstitution
Wang Lixian 1. College of Energy and Electrical Engineer, Hohai University 
Ma Hongzhong 1. College of Energy and Electrical Engineer, Hohai University 
Dai Feng 2. State Grid Jiangsu Electric Power Co. , Ltd. Maintenance Branch Company 
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中文摘要:
      为研究气体绝缘输电线路(GIL)设备局部放电引发的 GIL 壳体异常振动机理与特征,并对 GIL 局部放电趋势进行预 测。 首先,以尖端放电为例建立了 GIL 设备尖端放电模型与实验平台;其次,通过测取不同电压等级下尖端放电的脉冲电流信 号与异常振动信号,联合机电信号研究 GIL 异常振动行为的特征与机理;最后,建立鲸鱼优化算法-极限学习机(WOA-ELM)模 型对 GIL 局部放电趋势进行预测,并与 ELM 模型进行对比。 结果表明,GIL 尖端放电脉冲电流重复频率与异常振动信号频率 一致,GIL 局部放电与 GIL 壳体异常振动直接相关,且异常振动能量多集中在 1 600 ~ 2 800 Hz 且以 20 Hz 倍频分布为主;相较 于传统 ELM 模型,WOA-ELM 具有更为优越的预测能力,可以实现对 GIL 局部放电趋势的精确预测,为 GIL 局部放电趋势预测 提供了新的方法。
英文摘要:
      To study the mechanism and characteristics of abnormal vibration caused by partial discharge of GIL equipment, and predict the trend of partial discharge of GIL. Firstly, the tip discharge model and test platform of GIL equipment are established by taking the tip discharge as an example. Secondly, the characteristics and mechanism of GIL abnormal vibration behavior are studied by measuring the pulse current signal and abnormal vibration signal of tip discharge and combining with electromechanical signal. Finally, WOA-ELM model is established to predict the trend of GIL partial discharge and is compared with ELM model. The results show that the repetition frequency of discharge pulse current at GIL tip is consistent with the frequency of abnormal vibration signal, the partial discharge of GIL is directly related to the abnormal vibration of GIL shell, and the abnormal vibration energy is mainly concentrated in 1 600~ 2 800 Hz, and the frequency doubling distribution is mainly 20 Hz; Compared with the traditional ELM model, WOA-ELM has better prediction ability, which can realize the accurate prediction of GIL partial discharge trend, and provides a new method for GIL partial discharge trend prediction based on vibration signal.
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