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Study of predicting breakdown voltage of stator insulation in generator based on BP neural network

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【作者】 江裕熬张爱德刘丽兵杜预高乃奎彭宗仁

【Author】 Jiang Yuao,Zhang Aide,Liu Libing,Du Yu,Gao Naikui,Peng ZongrenState Key Laboratory of Electrical Insulation for Power Equipment,Xi’an Jiaotong University,Xi’an 710049,China.

【机构】 State Key Laboratory of Electrical Insulation for Power Equipment Xi’an Jiaotong UniversityState Key Laboratory of Electrical Insulation for Power EquipmentXi’an Jiaotong UniversityXi’an 710049China

【Abstract】 The breakdown voltage plays an important role in evaluating residual life of stator insulation in generator.In this paper,we discussed BP neural network that was used to predict the breakdown voltage of stator insulation in generator of 300MW/18kV.At first the neural network has been trained by the samples that include the varieties of dielectric loss factor tanδ,the partial discharge parameters and breakdown voltage.Then we tried to predict the breakdown voltage of samples and stator insulations subjected to multi-stress aging by the trained neural network.We found that it’s feasible and accurate to predict the voltage.This method can be applied to predict breakdown voltage of other generators which have the same insulation structure and material.

【基金】 This research was supported by the Key Technology R&D Programof State Power Corporation of China During the Tenth-Five-Year Plan Period.
  • 【文献出处】 Academic Journal of Xi’an Jiaotong University ,西安交通大学学报(英文版) , 编辑部邮箱 ,2007年01期
  • 【分类号】TM303
  • 【下载频次】69
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