首页|基于非负矩阵分解的高压断路器多重故障分析方法

基于非负矩阵分解的高压断路器多重故障分析方法

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  • 国家科技期刊平台
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高压断路器是电力网络的核心设备，直接关系到电力系统的安全可靠运行，机械故障是断路器常见的故障类型，本文提出了一种基于分量分离方法来检测断路器的多重机械故障，可实现在线实时监测。首先，给出了获取断路器机械声纹信号的模型及策略；然后，通过获取断路器运行的声纹信息数据，采用分量分离方法，将多重故障的声纹信号分解为单一分量的信号，在此基础上可以实现单一故障声纹信号特征的识别；最后，通过试验模拟和变电站现场采集到的断路器声纹信息数据进行验证，完成了高压断路器多重故障的辨识。研究结果表明：本文所提方法对断路器弹簧结构;内部组件松动等多重机械故障具有良好的辨识效果，同时，为高压断路器的实时在线监测提供了一种参考。
Analysis of multiple-faults of high-voltage circuit breakers based on non-negative matrix decomposition
High-voltage circuit breakers are the core equipment in power networks,and to a certain extent,are related to the safe and reliable operation of power systems.However,their core components are prone to mechanical faults.This study proposes a component separation method to detect multiple mechanical faults in circuit breakers that can achieve online real-time monitoring.First,a model and strategy are presented for obtaining mechanical voiceprint signals from circuit breakers.Subsequently,the component separation method was used to decompose the voiceprint signals of multiple faults into individual component signals.Based on this,the recognition of the features of a single-fault voiceprint signal can be achieved.Finally,multiple faults in high-voltage circuit breakers were identified through an experimental simulation and verification of the circuit breaker voiceprint signals collected from the substation site.The research results indicate that the proposed method exhibits excellent performance for multiple mechanical faults,such as spring structures and loose internal components of circuit breakers.In addition,it provides a reference method for the real-time online monitoring of high-voltage circuit breakers.

High voltage circuit breakerSignal separationMonitorMultiple faultsPower system

周永荣、马兆兴、陈昊、王瑞华

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State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks,Nanjing 211106,P.R.China

Nari Group Co.,Ltd.,Nanjing 211106,P.R.China

Qingdao University of Technology,School of Information and Control Engineering,Qingdao 266520,P.R.China

State Grid Nanjing Power Supply Company,Nanjing 211000,P.R.China

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高压断路器 分量分离 监测 多重故障 传感器

State Key Laboratory of Technology and Equipment for Defense against Power System Operational RisksNational Natural Science Foundation of ChinaNatural Science Foundation of Shandong Province

SGNR0000KJJS230213762203248ZR2020ME194

2024

10.1016/j.gloei.2024.04.006

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全球能源互联网(英文)

CSTPCDEI
ISSN：2096-5117
年,卷(期)：2024.7(2)
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