Threshold Denoising Analysis of Machinery Vibrating Signal Based on Wavelet Transform

An improved threshold algorithm for signal detection and denoising was developed based on wavelet transform. Two different thresholds are established according to the signal-to-noise ratio (SNR) of the signal. The measurements of the threshold vary with the wavelet scale, due to the different transformation characteristics of signals and noises at different scale. Through the decomposition of the signals, each high frequency coefficient was shrunk by a threshold, then restricted the signal. The experiments have shown it is more effective than other denoising methods (such as the Rigesure method, Squwolog method, Heursure method and Minimaxi method) when the signal is seriously disturbed by Gaussian white noise. It also indicates that this method gives better SNR performance than other wavelet denoising methods. All work is accomplished in MATLAB.