A weighted least square based data fusion method for precision measurement of freeform surfaces

摘要: Abstract The trend towards product miniaturisation and multi-functionality constitutes a driving force for the application of complex surfaces in many fields such as advanced optics. precision measurement these should be carried out at multiple scales, which process commonly involves several datasets obtained from different sensors. This paper presents weighted least square based multi-sensor data fusion method measurement. starts unifying coordinate frames measured using an intrinsic feature surface registration method. B-spline is used to fit linear model each identified overlapping area registered datasets, respectively. By forming common basis function, fitted models corresponding residuals are then combined construct system generate fused model. An analysis uncertainty propagation also given. Both computer simulation actual on various freeform conducted verify validity proposed results indicate that capable fusing with notable reduction uncertainty.