基于小波包技术和熵理论的航空故障电弧特征频段研究

Research on the Characteristic Frequency Band of Aviation Arc Fault Based on the Wavelet Packet and Entropy

  • 摘要: 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。

     

    Abstract: Aiming at the difficulties in measuring aviation series arc fault in AC system problems caused by wider spectrum range, a kind of analysis method of arc fault spectral characteristic was put forward by the combination of wavelet packet, information entropy and fast Fourier transform. Firstly, a series of arc fault simulation experiments of different loads in aviation AC system were carried out. Secondly, the best mother wavelet and decomposition level were chosen and characteristic band of the series arc fault current signal before and after arc burning was extracted by using wavelet packet technology, singularity entropy theory and negentropy theory. Finally, interharmonic feature of the arc fault current signal before and after arc burning was compared on characteristic band. The results showed that interharmonic feature in the characteridtic frequence band is more advantageous for the detection of arc fault than that over the entire frequency range.

     

/

返回文章
返回