多测头圆度估计的PCA误差分离方法

Separating Roundness Error with PCA in Estimation of Roundness of Multi Probe Head

针对多测头圆度估计过程中因干扰信号影响估计精度的问题,提出基于主成分分析的圆度误差分离方法。圆度误差测量数据包含多种信号成分,其中圆度误差信息只包含于表面形状误差信号中,主轴回转误差及噪声信号为干扰成分。利用主成分分析方法对圆度测量信号进行分解,实现多测头数据融合并实现各类信号成分分离;采用信号波数作为各信号成分的分离指标,实现形状误差信号提取,并利用其估计结构圆度误差。通过数值仿真分析验证方法的有效性。

Aiming at the estimation accuracy problem caused by interference signal in the roundness error measurement process,a new roundness error separation method based on principal component analysis is proposed. Roundness error measurement data include a variety of signal components,among which only the surface shape error signal contains roundness error information,while spindle rotation error signal and noise signal all are interference components. With the help of principal component analysis,the multi measurement data is fused and separated to various types of signal component. Taking signal wave number as the separation indicator,the shape error component extraction is achieved,and structural roundness error estimation is also realized. A numerical example is presented to demonstrate the efficacy of the method.