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作 者:赵明星 ZHAO Mingxing(Altay Power Supply Company,State Grid Xinjiang Electric Power Co.,Ltd.,Altay 836599,China)
机构地区:[1]国网新疆电力有限公司阿勒泰供电公司,新疆阿勒泰836599
出 处:《自动化仪表》2024年第12期24-28,共5页Process Automation Instrumentation
摘 要:变压器运行损耗的增加会破坏放电信号的可识别稳定性,导致变压器的运行性能降低。在考虑运行损耗的情况下,研究了变电站主变压器局部放电故障诊断方法。引入最大峭度解卷积(MKD)改进双树复小波变换(DTCWT),对变电站主变压器局部放电信号作去噪。采用多尺度熵和变分模态分解相结合的方法,提取变电站主变压器局部放电故障特征,并将全部特征输入反向传播(BP)神经网络分类器以实现故障诊断。试验结果表明,采用所提方法进行变电站主变压器局部放电故障诊断,可以得到高精度的局部放电故障诊断结果。所提方法具有较高的实际应用可靠性,有助于提高主变压器运行的稳定性。The increase of transformer operating loss will destroy the recognizable stability of discharge signal and lead to the reduction of transformer operation performance.The research of partial discharge fault diagnosis method of substation main transformer is carried out under the consideration of operating loss.The maximum kurtosis deconvolution(MKD)improved dual-tree complex wavelet transform(DTCWT)is introduced to denoise the partial discharge signals of substation main transformer.The combination method of multi-scale entropy and variational modal decomposition is used to extract the partial discharge fault features of the substation main transformer,and all the features are inputted into the back propagation(BP)neural network classifier to realize fault diagnosis.The experimental results show that using the proposed method for partial discharge fault diagnosis of substation main transformer can obtain highly accurate partial discharge fault diagnosis results.The proposed method has high reliability for practical application and helps to improve the stability of main transformer operation.
关 键 词:变电站 主变压器 局部放电 运行损耗 故障诊断 信号去噪 双树复小波变换
分 类 号:TH41[机械工程—机械制造及自动化]
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