An adaptive sampling method for complex surface detection based on triangular mesh simplification

Abstract

The invention provides a complex surface detection adaptive sampling method based on triangular mesh simplification, which calculates a curvature factor by calculating a quadratic error matrix and estimating a vertex Gaussian curvature and an average curvature to obtain an edge shrinkage error; the edge shrinkage error is obtained by calculating a quadratic error matrix and estimating a vertex Gaussian curvature and an average curvature. By judging the edge type to get the best shrinking target point, introducing the edge length constraints to optimize the distribution of sampling points, triangular mesh surface simplification under multi-constraint is realized, and then the simplified triangular mesh vertices are projected onto the design surface to get complex surface detection samplingpoints. The method is suitable for free-form surface detection sampling point planning with complex geometric characteristics, adopts multiple constraints to plan sampling point distribution, improvessampling point distribution defects under single constraint, reduces computational complexity based on discrete data, and improves measurement efficiency and accuracy.

Description

technical field [0001] The invention relates to the technical field of complex curved surface detection and sampling, in particular to an adaptive sampling method for complex curved surface detection based on triangular mesh simplification. Background technique [0002] Due to its superior geometric and mechanical properties, complex curved surfaces are widely used in aerospace, automobile, shipbuilding, mold and other industrial fields, and play an important role in achieving high physical properties such as system mechanical properties, optical properties, and fluid properties. In order to realize these functions, complex surfaces usually require high shape accuracy. In order to ensure that the processed surface meets the high-precision requirements, an effective processing quality inspection method is needed. Due to its irregularity and complexity, complex surfaces require a large number of sampling points to extract sufficient surface shape information. Coordinate meas...

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Problems solved by technology

Coordinate Measuring Machines (CMMs) are widely used in the field of precision measurement due to their high measurement accuracy, but the measurement efficiency is low due to point-by-point measurement with a contact probe

[0004] After searching the literature of the prior art, it was found that the Chinese patent "Adaptive Sampling Method Based on Machining Error Model and Hammersley Sequence" with the application number CN201711383515.4, the sampling method needs to integrate the curve, and the calculation is relatively complicated; the application number is CN201710454589.6's Chinese patent "An Intelligent Geometry Sampling Method Based on Three-Coordinate Freeform Surface", its sampling method is only carried out under a single curvature constraint

[0005] Therefore, the present invention intends to solve the outstanding problem that the existing sampling strategy for complex surface detection has defects in the distribution of sampling points under a single curvature constraint, and the calculation is relatively complex and the amount of calculation is large. sampling method

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