An Adaptive Sampling Method for Complex Surfaces

Abstract

An adaptive sampling method for complex surfaces, the content of which includes: determining the number of samples according to the sampling accuracy; incorporating projection points on complex surfaces into a given square area and converting them into two-dimensional projection points with density attributes; randomly generating samples at a set initial temperature points; search for sample points, calculate the mean value of the two generations of generators, and make them gradually approach the centroid point; use the variance function as a criterion to judge the quality of the solution, and set a random probability for the worsening solution to expand the solution space; update the generator, judge The coincidence accuracy of the occurrence element and the centroid point; select the occurrence element with the highest coincidence accuracy as the centroid point and return it as the global optimal solution; map the optimal solution back to the complex surface as the output of the optimal sampling solution. The invention has fast calculation speed and high efficiency, and improves the measurement efficiency and measurement precision of curved surface self-adaptive sampling.

Description

technical field [0001] The invention relates to an adaptive sampling method for curved surfaces, in particular to an adaptive sampling method for complex curved surfaces. The method is an adaptive sampling method based on the combination of MacQueen K-means algorithm and simulated annealing algorithm (MKSA). Background technique [0002] Complex surface parts are widely used in high-end manufacturing equipment fields such as ships, precision molds, aerospace, and national defense. Contact part inspections based on three-coordinate measuring machines and machine tool measurements need to specify limited sampling measurement points for measurement to detect processing quality. Surface adaptive sampling can effectively control the scale of collected measurement data on the basis of ensuring measurement accuracy, improve measurement efficiency, thereby reducing enterprise measurement costs and improving enterprise competitiveness. Therefore, the study of surface adaptive sampling...

AI Technical Summary

Problems solved by technology

[0007] In order to solve the deficiencies in the existing surface adaptive sampling method and further improve the fitting surface measurement accuracy and measurement efficiency of surface adaptive sampling, the present invention provides a complex surface adaptive sampling method, which is based on the MacQueen K-means algorithm Adaptive sampling method combined with simulated annealing algorithm (MKSA)

The method of the invention is mainly used to solve the self-adaptive sampling problem of complex curved surfaces that cannot be composed of elementary analytical curved surfaces

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