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现有小波基 ,如 Symmlet小波、Meyer小波等在应用时 ,普遍存在边界效应 ,在实际应用中必须增加数据采集窗的宽度 ,即增加分析信号的数据量 ,才能加以消除。文中根据 Donoho提出的构造平均插值小波基的方法 ,构造出 2 ,4,6,8阶平均插值小波 ,利用其边界校正的优点 ,在对信号进行分析时 ,可自动消除“边界”现象 ,而且故障信号在变换域内能量更集中 ,可大大提高故障检测的准确性。实例证明 ,平均插值小波能较好地用于电力系统故障实时检测。
Existing wavelet bases, such as Symmlet Wavelets and Meyer Wavelets, generally have boundary effects when applied. In practical applications, the width of the data acquisition window must be increased, that is, the data volume of the analyzed signals can be increased to be eliminated. According to Donoho’s method of constructing average interpolating wavelet bases, the average interpolation wavelets of order 2, 4, 6, 8 are constructed. By using the advantages of boundary correction, the phenomenon of “boundary” can be automatically eliminated when the signals are analyzed. Fault signal energy in the transform domain more focused, can greatly improve the accuracy of fault detection. The example shows that the mean interpolated wavelet can be used to detect power system faults in real time.