小波分解自适应滤波算法在表面粗糙度测量中的应用

Application of Wavelet Decomposition Self-Adaptive Filtering Algorithm in the Surface Roughness Measurement

在对机械加工零件进行表面粗糙度的测量过程中,采集的表面原始轮廓信号伴随的随机噪声对表面粗糙度测量值的影响非常大。为了滤除噪声,将小波分解自适应滤波算法应用到表面粗糙度测量领域,设计出用于表面粗糙度测量的自适应滤波器,并采用小波分解与最小均方实现算法,算法简便,易于实现。仿真结果表明:小波分解自适应滤波方法在表面粗糙度测量过程中有较好的降噪效果,具有一定的应用价值。

In process of the surface roughness measurement of the machined parts, the random noise accompanying with the original shape signal has great influence on the surface roughness measuring value. In order to filter out the noise, the wavelet decomposition adaptive filtering algorithm is used in the field of surface roughness measurement, the adaptive filter for the sur- face roughness measurement is designed, and the wavelet decomposition and the least mean square algorithm which is simple and easily realized are applied. The simulation results show that the wavelet decomposition adaptive filtering method has good noise reduction effect in the measurement of the surface roughness, and it has certain application value.