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高压断路器分合闸振动突变点自动化辨识技术

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为了及时发现潜在安全隐患,提出高压断路器分合闸振动突变点自动化辨识方法.将采集到的高压断路器分合闸振动信号输入到支持向量机中,以获得正常振动信号和疑似振动突变信号,提取出疑似振动突变信号;利用CEEMD AN分解算法获得各疑似振动突变信号的分量,并根据信号分量的方差贡献率保留重要分量;对重要分量的谱峭度展开计算,并设置谱峭度阈值,将分量谱峭度大于阈值的信号判定为振动突变信号,以此完成振动突变点的自动化辨识.实验结果表明,该方法的信号分量提取性能较高、突变点辨识效果较好.
Automatic Identification Technology for Sudden Vibration Points During the Opening and Closing of High-voltage Circuit Breakers
In order to timely detect potential safety hazards,an automated identification method for the sudden change point of high-voltage circuit breaker opening and closing vibration is proposed.Input the collected high-voltage circuit breaker opening and closing vibration signals into the support vector machine to obtain normal vibration signals and suspected vibration mutation signals,and extract suspected vibration mutation signals.Using the CEEMDAN decompo-sition algorithm to obtain the components of each suspected vibration mutation signal,and retaining important compo-nents based on the variance contribution rate of the signal components.Calculate the spectral kurtosis of important components and set a spectral kurtosis threshold.Signals with component spectral kurtosis greater than the threshold are identified as vibration mutation signals,thus completing the automated identification of vibration mutation points.The experimental results show that the method has high performance in signal component extraction and good identi-fication effect for mutation points.

high voltage circuit breaker opening and closingidentification of vibration mutation pointssupport vector machineCEEMDAN decompositionspectral kurtosis

李敬光、刘宏、罗松林、刘树安

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广东电网有限责任公司东莞供电局,东莞 523008

高压断路器分合闸 振动突变点辨识 支持向量机 CEEMDAN分解 谱峭度

2024

自动化与仪表
天津市工业自动化仪表研究所 天津市自动化学会

自动化与仪表

CSTPCD
影响因子:0.548
ISSN:1001-9944
年,卷(期):2024.39(12)