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针对航空交流系统串联型故障电弧电流信号频谱范围宽、检测困难的问题,提出了小波包理论、信息熵理论与傅里叶变换相结合提取故障电弧特征频段的方法。首先开展了不同类型负载线路的航空交流系统串联型故障电弧模拟试验。其次,利用小波包技术、奇异熵理论和负熵理论,选择最优的小波母函数和分解层数,并对发生故障电弧前后的电流信号进行特征频段的提取。然后,对比特征频段下故障电弧发生前后电流信号的间谐波特征。结果表明,特征频段上的间谐波特征比没有经过特征频段提取计算出的间谐波特征更有利于故障电弧的检测。
Aiming at the problem of wide spectrum range and difficult detection of arcing current signal in AC fault series, a method of combining wavelet packet theory, information entropy theory and Fourier transform to extract fault arc characteristic frequency band is proposed. First of all, carried out a series of different types of load line of the AC system fault simulation arc series. Secondly, using the wavelet packet technique, the singular entropy theory and the negative entropy theory, the optimal wavelet mother function and the number of decomposition layers are selected, and the characteristic frequency band of the current signal before and after the fault arc is extracted. Then, the interharmonic characteristics of the current signal before and after the occurrence of the fault arc in the characteristic frequency band are compared. The results show that the characteristics of interharmonics in the characteristic frequency band are more conducive to the detection of fault arcing than those of the interharmonics without the characteristic frequency band extraction.