基于声纹特征EMD提取的GIS断路器机械故障诊断方法研究

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中图分类号：TM561 文献标志码：A doi：10.3969/j.issn.1006-0316.2025.08.011

文章编号：1006-0316（2025）08-0069-06

AGISCircuitBreakerMechanical FaultDiagnosisMethodBased on EMDExtractionof Voiceprint Features

GUOBin，DIAOWenzheng，WUXiaorui （SDEE Hitachi High-Voltage Switchgear Co.，Ltd.， Jinan， China）

Abstract ： The voiceprint signal of GIS circuit breaker usually has multiple frequency components and complex nonlinear characteristics.The direct analysis can only capture some of the features，thereby reducing the efficiency offault diagnosis.This paper proposes a GIS circuit breaker mechanical fault diagnosis method based on EMD extraction of voiceprint features.The GIS circuit breaker voiceprint signal is processed by EMD algorithm，and the complex signal is decomposed into multiple IMFcomponents.ThenRMS energyand linear discriminant analysisare used to extractkeyfeatures，and the feature set with the most eficient classification is selected bytheRelief-Falgorithm.Accordingly，the thresholdof edge diagnosis features is established，anda clasificationalgorithm model is introduced to evaluate the matching degree between the test samples and the known fault samples，so as to realize the mechanical fault diagnosis of GIS circuit breaker.The experimental results show that the proposed method can accurately match the actual diagnosis types among various simulated types of GIS circuit breaker mechanical fault. It also shows fast diagnosis speed under diferent fault severity， which significantly improves the diagnosis efficiency.

Keywords ：EMD decomposition i voiceprint features; feature extraction;GIS circuit breaker; fault diagnosis

随着电力系统的不断发展，高压断路器的机械故障诊断成为了确保电网稳定运行的关键环节。（剩余4743字）