Classification of Partial Discharge Level in Switchgear Cabinet Based on the Improved Association Rules Mining Algorithm

ZHENG Wendong; HUANG Chengjun; YANG Ning; JIANG Xiuchen

doi:10.13296/j.1001-1609.hva.2014.02.008

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Classification of Partial Discharge Level in Switchgear Cabinet Based on the Improved Association Rules Mining Algorithm

更新时间：2025-04-26

- Classification of Partial Discharge Level in Switchgear Cabinet Based on the Improved Association Rules Mining Algorithm
- High VoltageApparatus Vol. 50, Issue 2, Pages: 23-28(2014)
- 作者机构：
  
  1. 上海交通大学
  2. 中国电力科学研究院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2014.02.008
  CLC： TM591
- Published：2014
- 稿件说明：
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[1]郑文栋,黄成军,杨宁,江秀臣.基于新型关联规则算法的开关柜局放程度分类研究[J].高压电器,2014,50(02):23-28.

ZHENG Wendong, HUANG Chengjun, YANG Ning, et al. Classification of Partial Discharge Level in Switchgear Cabinet Based on the Improved Association Rules Mining Algorithm[J]. High voltageapparatus, 2014, 50(2): 23-28.
[1]郑文栋,黄成军,杨宁,江秀臣.基于新型关联规则算法的开关柜局放程度分类研究[J].高压电器,2014,50(02):23-28. DOI： 10.13296/j.1001-1609.hva.2014.02.008.

ZHENG Wendong, HUANG Chengjun, YANG Ning, et al. Classification of Partial Discharge Level in Switchgear Cabinet Based on the Improved Association Rules Mining Algorithm[J]. High voltageapparatus, 2014, 50(2): 23-28. DOI： 10.13296/j.1001-1609.hva.2014.02.008.

摘要

为对开关柜绝缘状态进行评估

文中介绍了一种新型的关联规则数据挖掘（ARM）算法

用于识别开关柜局部放电的严重程度。该算法采用模糊C均值聚集（FCM）的方法划分局部放电特征量区间

基于改进型Apriori寻找满足最小支持度和最小可信度的候选集

对候选集进行递推和多次检索以产生用于分类的关联规则库。基于关联规则库对采集的10 kV开关柜中的多组针尖电晕局部放电信号进行模糊推理

结果表明采用关联规则的局部放电分类识别率高

分类结论准确

为开关柜绝缘状态评估提供了一定的理论依据和实际应用价值。

Abstract

An improved association rules mining（ARM） algorithm is proposed for classification and recognition of partial discharge level to estimate the insulation status in switchgear cabinet.The method of fuzzy C-means clustering（FCM） is used to divide the range of partial discharge characteristic amounts.The Apriori algorithm is improved to find the candidate item sets which meet the minimum support and the minimum confidence.Recursion and retrieval are executed repeatedly to establish an association rule base for classification.A partial discharge experiment platform for 10 kV switchgear cabinet is set up

and several groups of corona partial discharge signals at different severity levels are detected for fuzzy reasoning.The results show that the signals can be classified into three severity levels accurately.The proposed classification method may benefit insulation status estimation and partial discharge detection.

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