Sampling optimization for 3D surface measurement. Part I: Sampling area optimization based on areal texture parameter analysis

• Published in: Measurement : journal of the International Measurement Confederation 2022-11, Vol.203, p.111972, Article 111972
• Main Authors: Song, Xiao-Fei, Tang, Hao, Zhang, Yi-Yin, Zheng, Shu-Xian
• Format: Article
• Language: English
• Subjects: Areal texture parameter; Sampling area; Sampling optimization; Surface characterization
• ISSN: 0263-2241; 1873-412X
• DOI: 10.1016/j.measurement.2022.111972

[Display omitted] •Optimal sampling areas in 3D surface measurement were proposed for the surfaces with different surface height ranges.•An isotropic surface requires a smaller sampling area compared to an anisotropic surface in the same roughness range.•The optimized sampling areas were verified by experimentally machined engineering surfaces.•The optimized sampling areas provide guidance of standardizing sampling parameter selection in 3D surface measurement for comparability. Surface roughness characterization is associated with sampling parameters during measurement, but little was reported on sampling scale selection for 3D surface topography measurement. This study aimed to optimize sampling areas for four surfaces with different surface height ranges for comparability and repeatability of areal texture measurement. Two kinds of isotropic and anisotropic 3D random surfaces were simulated and generated based on fast Fourier transform (FFT) and autocorrelation function. The availability of the two simulated surfaces was verified by actual surfaces machined using polishing and grinding. The surface heights parameters of Sq and Sz were selected as evaluation parameters to determine the optimal sampling areas based on the analysis for coefficients of variation of five typical areal texture parameters of Sq, Sz, Sku, Ssk, and Sal. For each surface, fifty sampling areas with different side lengths were selected to evaluate the response of Sq and Sz to the side length of sampling area. The results show anisotropic surfaces needed larger sampling areas than isotropic surfaces under the same roughness range. Four optimal sampling areas were determined corresponding to four different Sq ranges for isotropic and anisotropic surfaces, respectively. Finally, four surfaces corresponding to different Sq ranges were machined using four burs with different abrasive grits. Based on the recommended optimal sampling areas, their 3D surface topographies and areal texture parameters were measured. The minimum standard deviation (SD) analysis was performed on the measurement results, which verified the validity of the recommended optimal sampling areas. These optimal sampling areas provide practical guidance of standardizing sampling parameter selection for repeatability and comparability in areal texture parameters measurement of 3D surface measurements.