基于小波去噪与随机森林的配电网高阻接地故障半监督识别方法
针对配电网高阻接地故障识别易受噪声干扰、无标签数据难以利用的难题,提出一种基于小波去噪与随机森林的高阻接地故障半监督识别方法.区别于监督式学习方法仅利用标签数据,基于协同训练方法能够充分利用有标签数据与无标签数据.首先,使用小波阈值去噪算法消除零序电流中的噪声.其次,采用波峰波谷故障启动算法判断线路是否发生故障或扰动事件.运用小波变换提取零序电流的小波系数作为故障特征.最后,基于小波系数故障特征构建两个随机森林作为半监督分类器进行协同训练,从而实现高阻接地故障的检测识别.仿真结果表明,所提配电网高阻接地故障半监督识别方法可以充分挖掘配电网既有的故障案例中无标注数据蕴含的关键特征,从而提高故障分...
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| Published in | 电力系统保护与控制 Vol. 50; no. 20; pp. 79 - 87 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
南方电网科学研究院,广东 广州 510663%广东电网有限责任公司东莞供电局,广东 东莞 530600%福州大学电气工程与自动化学院,福建 福州 350108
16.10.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-3415 |
| DOI | 10.19783/j.cnki.pspc.226429 |
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| Abstract | 针对配电网高阻接地故障识别易受噪声干扰、无标签数据难以利用的难题,提出一种基于小波去噪与随机森林的高阻接地故障半监督识别方法.区别于监督式学习方法仅利用标签数据,基于协同训练方法能够充分利用有标签数据与无标签数据.首先,使用小波阈值去噪算法消除零序电流中的噪声.其次,采用波峰波谷故障启动算法判断线路是否发生故障或扰动事件.运用小波变换提取零序电流的小波系数作为故障特征.最后,基于小波系数故障特征构建两个随机森林作为半监督分类器进行协同训练,从而实现高阻接地故障的检测识别.仿真结果表明,所提配电网高阻接地故障半监督识别方法可以充分挖掘配电网既有的故障案例中无标注数据蕴含的关键特征,从而提高故障分类准确率,具有较强的准确性和灵敏性. |
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| AbstractList | 针对配电网高阻接地故障识别易受噪声干扰、无标签数据难以利用的难题,提出一种基于小波去噪与随机森林的高阻接地故障半监督识别方法.区别于监督式学习方法仅利用标签数据,基于协同训练方法能够充分利用有标签数据与无标签数据.首先,使用小波阈值去噪算法消除零序电流中的噪声.其次,采用波峰波谷故障启动算法判断线路是否发生故障或扰动事件.运用小波变换提取零序电流的小波系数作为故障特征.最后,基于小波系数故障特征构建两个随机森林作为半监督分类器进行协同训练,从而实现高阻接地故障的检测识别.仿真结果表明,所提配电网高阻接地故障半监督识别方法可以充分挖掘配电网既有的故障案例中无标注数据蕴含的关键特征,从而提高故障分类准确率,具有较强的准确性和灵敏性. |
| Author | 白浩 郭谋发 李巍 雷金勇 邵向潮 高健鸿 潘姝慧 |
| AuthorAffiliation | 南方电网科学研究院,广东 广州 510663%广东电网有限责任公司东莞供电局,广东 东莞 530600%福州大学电气工程与自动化学院,福建 福州 350108 |
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| Keywords | 小波变换 配电网 半监督学习 随机森林 高阻接地故障 |
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| Publisher | 南方电网科学研究院,广东 广州 510663%广东电网有限责任公司东莞供电局,广东 东莞 530600%福州大学电气工程与自动化学院,福建 福州 350108 |
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| Title | 基于小波去噪与随机森林的配电网高阻接地故障半监督识别方法 |
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