基于非负矩阵分解的高压断路器多重故障分析

IF 1.9 Q4 ENERGY & FUELS Global Energy Interconnection Pub Date : 2024-04-01 DOI:10.1016/j.gloei.2024.04.006
Yongrong Zhou , Zhaoxing Ma , Hao Chen , Ruihua Wang
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引用次数: 0

摘要

高压断路器是电网的核心设备,在一定程度上关系到电力系统的安全可靠运行。然而,其核心部件容易发生机械故障。本研究提出了一种检测断路器多重机械故障的元件分离方法,可实现在线实时监测。首先,介绍了获取断路器机械声纹信号的模型和策略。随后,使用元件分离法将多个故障的声纹信号分解为单个元件信号。在此基础上,可以实现对单个故障声纹信号特征的识别。最后,通过对变电站现场采集的断路器声纹信号进行实验模拟和验证,识别了高压断路器的多重故障。研究结果表明,所提出的方法对于多种机械故障(如断路器的弹簧结构和松动的内部组件)具有卓越的性能。此外,它还为高压断路器的实时在线监测提供了一种参考方法。
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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.

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来源期刊
Global Energy Interconnection
Global Energy Interconnection Engineering-Automotive Engineering
CiteScore
5.70
自引率
0.00%
发文量
985
审稿时长
15 weeks
期刊最新文献
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