基于小波变换和S-G滤波的多尺度平滑预处理方法

Multiscale smoothing preprocessing method based on wavelet transform and S-G filtering

针对模锻压力机在高压、高温、高速和高振动等恶劣环境下长时间服役时,其信号存在非线性、不平稳、易被强烈背景噪声干扰等问题,提出一种基于小波变换与S-G滤波的多尺度平滑预处理方法。其中,小波变换方法对信号进行多尺度分解,有效捕捉信号的特征和动态变化,并通过调整小波基函数和S-G滤波器参数来满足多尺度信号的特性和去噪需求;逆离散小波变换用于重构信号,实现信号的完整、连续和平滑。结果表明:该方法可在多尺度水平上有效地消除噪声的同时保留有效的信息,优于传统的移动平均法、S-G滤波、小波变换强制消噪处理法和门限消噪方法。

For the problem that the signal of the die forging press was affected by nonlinearity,instability,and strong background noise interference in harsh environments such as high pressure,high temperature,high speed,and high vibration during long-term operation,a multiscale smoothing preprocessing method based on wavelet transform and S-G filtering was proposed.Among them,the wavelet transform method decomposed the signal in multiscal to effectively capture the characteristics and dynamic changes of the signal,adjusted the wavelet basis function and S-G filter parameters to meet the characteristics of the multiscale signal and denoising requirements.The inverse discrete wavelet transform was used to reconstruct the signal to realize the integrity,continuity,and smoothness of the signal.The results show that this method can effectively eliminate noise at the multiscale level while retaining effective information,which is superior to traditional moving average method,S-G filtering,wavelet transform forced denoising processing method and threshold denoising method.