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基于振动信号EMD-HT时频分析的变压器有载分接开关故障诊断
引用本文:张惠峰,马宏忠,陈凯,王春宁,高鹏. 基于振动信号EMD-HT时频分析的变压器有载分接开关故障诊断[J]. 高压电器, 2012, 48(1): 76-81
作者姓名:张惠峰  马宏忠  陈凯  王春宁  高鹏
作者单位:1. 广东电网公司教育培训评价中心,广州,510520
2. 河海大学能源与电气学院,南京,210098
3. 江苏省电力公司南京供电公司,南京,210008
基金项目:江苏省电力公司重点科技项目
摘    要:把一列时间序列数据通过经验模态分解(empirical mode decomposition,EMD)为本征模态函数组(intrinsic mode function,IMF),然后进行希尔伯特变换(hilbert transformation,HT)得到频谱的信号时频分析方法引用到变压器有载分接开关切换机构的振动信号分析领域。笔者介绍了该方法的理论和算法。首先采用仿真信号对该方法进行仿真验证,然后把一实测的有载分接开关故障振动信号进行基于EMD-HT方法的时频分析。通过仿真和实例信号分析结果说明,用EMD-HT时频分析方法对变压器有载分接开关的振动信号进行故障特征提取是有效的。

关 键 词:有载分接开关  振动信号  经验模态分解  希尔伯特变换  时频分析

Fault Diagnosis of Power Transformer On-load Tap Changer Based on EMD-HT Analysis of Vibration Signal
ZHANG Hui-feng , MA Hong-zhong , CHEN Kai , WANG Chun-ning , GAO Peng. Fault Diagnosis of Power Transformer On-load Tap Changer Based on EMD-HT Analysis of Vibration Signal[J]. High Voltage Apparatus, 2012, 48(1): 76-81
Authors:ZHANG Hui-feng    MA Hong-zhong    CHEN Kai    WANG Chun-ning    GAO Peng
Affiliation:1.Education and Evaluation Center of Guangdong Power Grid Corporation,Guangzhou 510520,China; 2.College of Energy and Electrical Engineering,Hehai University,Nanjing 210098,China; 3.Nanjing Power Supply Company,Jiangsu Electric Power Company,Nanjing 210008,China)
Abstract:A list of time series data is decomposed into an eigen modal functions group through the empirical mode decomposition(EMD),then Hilbert transformation(HT) is adopted to get the signal frequency spectrum analysis method of reference to the transformer on-load tap changer switching mechanism of vibration signal analysis field.The authors introduces the theory and method of the algorithm,the first of the method of simulation signal simulation test,and then apply the time-frequency analysis which is based on the method of EMD-HT to a testing fault vibration signal analysis of the switching mechanism of the OLTC.Through the simulation signal and the example analysis shows that,with EMD-HT time-frequency analysis method for transformer on-load tap-changer vibration signal of the fault feature extraction is effective.
Keywords:OLTC  vibration signal  empirical mode decomposition  Hilbert transformation  time-frequency analysis
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