不同电极材料条件下改进Catboost算法的直流故障电弧检测算法

孟羽; 陈思磊; 吴子豪; 王辰曦; 李兴文

doi:10.7652/xjtuxb202203013

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不同电极材料条件下改进Catboost算法的直流故障电弧检测算法

更新时间：2025-07-09

- 不同电极材料条件下改进Catboost算法的直流故障电弧检测算法
- A DC Arc Fault Detection Method Based on Catboost Algorithm for Different Electrode Materials
- 西安交通大学学报 2022年56卷第3期页码：124-134
- 作者机构：
  
  西安交通大学电力设备电气绝缘国家重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2021-07-31。作者简介: 孟羽(1997—),男,博士生;李兴文(通信作者),男,教授,博士生导师。基金项目: 国家电网有限公司总部管理科技项目(SGSNKYOOKJJS1900038)
- DOI：10.7652/xjtuxb202203013
  中图分类号： O441.1
- 网络首发：2022-03-10，
  
  纸质出版：2022
- 稿件说明：
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孟羽, 陈思磊, 吴子豪, 等. 不同电极材料条件下改进Catboost算法的直流故障电弧检测算法[J]. 西安交通大学学报, 2022,56(3):124-134.

A DC Arc Fault Detection Method Based on Catboost Algorithm for Different Electrode Materials[J]. 2022, 56(3): 124-134.
孟羽, 陈思磊, 吴子豪, 等. 不同电极材料条件下改进Catboost算法的直流故障电弧检测算法[J]. 西安交通大学学报, 2022,56(3):124-134. DOI： 10.7652/xjtuxb202203013.

A DC Arc Fault Detection Method Based on Catboost Algorithm for Different Electrode Materials[J]. 2022, 56(3): 124-134. DOI： 10.7652/xjtuxb202203013.

摘要

为了研究直流系统内不同电极材料对故障电弧检测造成的干扰

针对性地解决多种电极材料下故障电弧检测的误动与拒动问题

提出了改进Catboost算法的直流故障电弧检测算法。搭建直流故障电弧实验平台

以拉弧的方式获取了6种电极材料条件下的直流故障电弧数据

通过构建故障电弧检测特征评价指标

采用小波变换方法在不同电极材料条件下更有效地提取故障电弧时频特征; 分析不同电极材料对直流故障电弧检测特征、算法效率的影响

指出检测特征指标与材料熔点、电阻率呈正相关关系; 提出的算法相较于现有的阈值比较算法和Adaboost算法提高了电弧检测范围

有效解决了纯铝电极材料下难以准确检测电弧的问题。该算法在6种不同电极材料下均能实现1.5 s内对电弧的快速检测

检测准确率达到100%

满足UL1699B标准要求。

Abstract

In order to study the interference of different electrode materials on arc fault detection in DC system

and to solve the malfunction problems of arc fault detection with avarious electrode materials

a DC arc fault detection algorithm based on Catboost algorithm is proposed. A DC arc fault experiment platform is built and the DC arc fault data from 6 electrode materials are obtained by the pulling-apart method. Through constructing the evaluation index of the arc fault detection characteristic

the wavelet transform method is used to extract time-frequency characteristics of arc faults more effectively for different electrode materials. The influences of different electrode materials on DC arc fault detection characteristics and efficiency of the algorithms are analyzed

and it is pointed out that the detection characteristic index has a positive correlation with the melting point and resistivity of electrode material. Compared with the existing threshold comparison method and the Adaboost algorithm

the proposed algorithm improves the range of arc fault detection and effectively solves the problem that it is difficult to accurately detect arc faults using pure aluminum electrode material. This algorithm can realize rapid detection of arc faults within 1.5 s for the 6 different electrode materials

and the detection accuracy reaches 100%

which meets the requirements of UL1699B standard.

关键词

Keywords

references

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