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Three-coordinate freeform surface based intelligent geometric sampling method

A three-coordinate, curved surface technology, applied in measuring devices, instruments, etc., can solve the problems of shape error, ignore the surface features of the machined surface, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2017-10-20
TIANJIN UNIV
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  • Application Information

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Problems solved by technology

However, this type of method ignores the surface features of the machined surface, and the surface features play a great role in the machining process. Taking the curvature of the free-form surface as an example, the tool contact changes caused by the machining of different curvature curves will bring shape error [3]

Method used

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  • Three-coordinate freeform surface based intelligent geometric sampling method
  • Three-coordinate freeform surface based intelligent geometric sampling method
  • Three-coordinate freeform surface based intelligent geometric sampling method

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Embodiment Construction

[0027] The present invention will be further described below in conjunction with the accompanying drawings.

[0028] 1. About NURBS surfaces

[0029] NURBS (Non-Uniform Rational B-Splines) are widely used in the field of surface design and reconstruction. Because of the widespread use of NURBS in the CAD / CAM / CAE field and in international standards (IGES, STEP, PHIGS and OpenGL), NURBS surfaces are used in this embodiment to represent freeform surfaces.

[0030] A NURBS surface of order p in the u direction and order q in the v direction can be expressed as:

[0031]

[0032] Among them, P i,j is the control point, ω i,j is the weight of each control point, u and v are parameters between [0,1], i=0,1,2,3...m, j=0,1,2,3...n,N i,p (u),N j,q (v) is the basis function of the non-uniform rational B-spline determined by the point vector, which can be calculated by the De Boor-Cox recursive formula, where u i is a point vector; the same basis functions in the v direction can...

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Abstract

The invention discloses a three-coordinate freeform surface based intelligent geometric sampling method, which comprises the steps of (1) dispersing a curved surface into transversal lines along a u-direction and a v-direction so as to be approximated as a surface; (2) sampling along the v-direction, enabling sampled sampling points to reflect features of the v-direction, acquiring a point set, and connecting the point set along the u-direction to acquire a group of curves; (3) separating the sampling points along the u-direction on the curves, and acquiring the number of the sampling points of nu*nv; and (4) optimizing an adaptive factor by using a genetic algorithm so as to improve the measurement accuracy. According to the method, the adaptive factor is utilized to regulate the adaptation and uniform distribution of sample allocation, and the adaptive weighting factor is optimized through the genetic algorithm so as to improve the measurement accuracy. Meanwhile, the effectiveness of the method is proved through designing a freeform surface with an error and being compared with other three known indication methods.

Description

technical field [0001] The invention relates to the field of collective measurement of machining errors, in particular to an intelligent geometric sampling method based on a three-coordinate free-form surface. Background technique [0002] Freeform surfaces are widely used in engineering, and the measurement of freeform surface features is the basis for quality control and fault diagnosis processes [1] . The sampling process includes two parts: setting the number of sampling points and selecting the distribution strategy of sampling points [2] . However, in many cases the distribution of sampling points is a major factor in determining the number of sampling points. Therefore, the current research mainly focuses on the sampling point distribution strategy. Among the sampling methods, it is more common to distribute the sampling points in a uniform pattern, because this method can have the advantages of simplified algorithm, fast calculation and sufficient representative ...

Claims

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Application Information

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IPC IPC(8): G01B21/20
CPCG01B21/20
Inventor 何改云庞凯瑞桑一村孙静静刘晨辉
Owner TIANJIN UNIV
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