Development Stage Recognition of Partial Discharge in Oil-paper Insulation Based on Probabilistic Neural Network

SUN Changhai; SU Xiaomin; LI Tianlun; WANG Chunfeng; MA Shuang; HANG Huifang

doi:10.13296/j.1001-1609.hva.2022.01.018

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Development Stage Recognition of Partial Discharge in Oil-paper Insulation Based on Probabilistic Neural Network

更新时间：2025-04-26

- Development Stage Recognition of Partial Discharge in Oil-paper Insulation Based on Probabilistic Neural Network
- High VoltageApparatus Vol. 58, Issue 1, Pages: 138-147(2022)
- 作者机构：
  
  大连理工大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2022.01.018
  CLC： TM855;TP183
- Published：2022
- 稿件说明：
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SUN Changhai, SU Xiaomin, LI Tianlun, et al. Development Stage Recognition of Partial Discharge in Oil-paper Insulation Based on Probabilistic Neural Network[J]. High voltageapparatus, 2022, 58(1): 138-147.
DOI：

SUN Changhai, SU Xiaomin, LI Tianlun, et al. Development Stage Recognition of Partial Discharge in Oil-paper Insulation Based on Probabilistic Neural Network[J]. High voltageapparatus, 2022, 58(1): 138-147. DOI： 10.13296/j.1001-1609.hva.2022.01.018.

摘要

采用阶梯升压法进行油纸绝缘沿面放电与气隙放电实验

根据放电发展过程的差异将局部放电划分成4个阶段:放电初始阶段、放电发展阶段、放电稳定阶段和临近击穿阶段

分析两种模式下放电特征参量的发展规律。提取放电相位分布(PRPD)图谱的29个统计特征参量

通过局部线性嵌入算法降维得到新的六维特征参量

采用概率神经网络(PNN)算法对两种放电模式下油纸绝缘放电发展阶段进行识别

并与广义回归神经网络(GRNN)模型以及反向传播神经网络(BPNN)模型进行比较

发现其识别结果更加准确。

Abstract

The step-up method is used to perform the experiments of surface discharge and air-gap discharge in oilpaper insulation. According to the difference of discharge development process

the partial discharge is divided into four stages:initial stage

development stage

stabilization stage and near breakdown stage of discharge. And the development rules of discharge characteristic parameters under the two modes are analyzed.Twenty-nine statistical characteristic parameters of phase resolved partial discharge（PPRD）are extractedand new six-dimensional characteristic parameter is obtained by using the dimensionality reduction of local linear embedding algorithm. The probabilistic neural network（PNN）algorithm is adopted to identify discharge development stages of oil-paper insulation under two discharge modes and is compared with the generalized regression neural network（GRNN）model and the back-propagation neural network（BPNN）model

finding its recognition resultis more accurate.

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