基于小波分析的动平衡机不平衡量提取方法研究

Study on unbalanced signal extraction from a dynamic balancing machine based on wavelet analysis

针对动不平衡信号周期性强且伴随有强烈的背景噪声,提出一种基于小波细节系数自相关性分析的分层阈值降噪法,该方法对信号进行离散小波变换,将信号分解为近似系数和细节系数,求出各层细节系数的自相关序列,根据序列是否呈白噪声自相关特性确定该层阈值。通过模拟的方法对含噪振动信号进行了试验,结果表明该方法具有较好的降噪效果。最后,对基于自相关序列分析的分层阈值降噪法在轮胎动平衡测试系统的实际应用进行了研究。实际应用表明,该方法适合动平衡测量,满足高精度要求。

The unbalanced signal is periodic and carries intense background noise.In view of these characteristics,a de-noising method using a multilevel threshold based on the analysis of the autocorrelation of detailed coefficients was proposed.This method uses the discrete wavelet transform technique to decompose the signal into approximations and details.The autocorrelation sequences of the detailed coefficients were determined.According to whether the sequence reflects the autocorrelation of white noise,the threshold was determined.The results of experiments and the application in practical dynamic balancing measurement system indicate the presented method was fit to apply in dynamic balancing measurement,which satisfies the requirement of high precision.