小波分析在信号处理中的应用

Application of Wavelet Analysis in the Signal Processing

在信号奇异点检测中,首先对信号进行多尺度小波分解。然后对高频部分进行重构,确定模极大值点位置,从而确定出奇异点位置。在例子中检测含有故障信息的电压信号,结果表明信号分解的细节部分均能清晰地显示出奇异点的准确位置。在信号消噪中,首先将信号进行多尺度小波分析。然后通过设置阈值的方法对高频子带进行处理,接着进行重构。在例子中对染噪的电压信号进行消噪处理,结果表明阈值的选取直接关系到消噪的质量。

In the detection of signal singularity,the signal was decomposed by multi-scale wavelet at first,and each sub-band coefficient of the signal was obtained.Then the high-frequency parts was reconstructed,and the location of maximum modulus points was determined,so the location of the signal singularity was determined.The voltage signal containing the fault information was detected in the case,and the re sults show that the details of part of the signal decomposition can clearly show the exact location of singular points.In the course of signal de-noising,the signal was analyzed by multi-scale wavelet at first,and each sub-band of signal was obtained.Then the high frequency subband were processed by the threshold setting method,and the processed signal was reconstructed next.The polluted voltage signal was denoised in the case,and the results show that threshold selection is directly related to the quality of de-noising.