基于小波理论的异步电动机故障信号的消噪方法

摘要

The signal denoising method based on the wavelet transform is analyzed according to the early fault diagnosis of asynchronous motor. The signal is spread according to the different frequency band. The wavelet transform modulus is quantified through the float threshold value. The result shows this method can eliminate the most noises and keep the curve profile of the original signal in acumination transform. It can accurately diagnose the asynchronous motor′s emergency fault signal and achieve the preferable denoising effect.%通过对异步电动机早期故障诊断，分析了基于小波变换的信号消噪方法，根据不同频带将信号展开，并选择浮动阈值对小波变换系数进行量化，结果表明，这种方法可消除大部分噪音并保留原信号尖锐变化的曲线轮廓，对异步电动机突发故障信号诊断准确，并能达到更好的降噪效果。