Measurement and data processing method of machined surface for assembly performance prediction

The assembly process cannot meet the increasing demands with the conventional method. To obtain an optimal assembly performance, the machined surface should be reconstructed, and further analysis should be conducted to provide a direct guidance for the assembling process. Surface topography can be represented by a sufficient number of points; however, the measurement of dense points would be time-consuming. In this study, the measured points are arranged in a nonuniform manner, and processed by interpolation for the reconstruction of the actual surface and the prediction of the assembly performance. Point clouds processed by 4 interpolation methods were used to verify the proposed method. The sampling strategy and data processing was concluded to be accurate; measurement time was significantly decreased compared to the dense points. It is proposed that the three indexes should be taken into consideration when the method is used to process the measurement data of different machined surfaces.