Mesh-based adaptive planning for complex surface accurate measurement

Jian-hua YE; Cheng-hui GAO; Shou-jin ZENG

doi:10.3788/OPE.20192707.1632

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Mesh-based adaptive planning for complex surface accurate measurement

Information Sciences | 更新时间：2020-08-13

- Mesh-based adaptive planning for complex surface accurate measurement
- Optics and Precision Engineering Vol. 27, Issue 7, Pages: 1632-1639(2019)
- 作者机构：
  
  1.福建工程学院机械与汽车工程学院，福建福州 350118
  2.福州大学机械工程及自动化学院，福建福州 350116
  3.福建工程学院先进制造生产力促进中心，福建福州 350118
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20192707.1632
  CLC： TP391.7
- Received：17 October 2018，
  
  Accepted：27 December 2018，
  
  Published：15 July 2019
- 稿件说明：
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Jian-hua YE, Cheng-hui GAO, Shou-jin ZENG. Mesh-based adaptive planning for complex surface accurate measurement[J]. Optics and precision engineering, 2019, 27(7): 1632-1639.
DOI：

Jian-hua YE, Cheng-hui GAO, Shou-jin ZENG. Mesh-based adaptive planning for complex surface accurate measurement[J]. Optics and precision engineering, 2019, 27(7): 1632-1639. DOI： 10.3788/OPE.20192707.1632.

摘要

检测点的布局优化是复杂曲面类零件加工误差检测的关键。针对由多张不同特征曲面复合而成的零件模型整体的自适应测点规划困难问题，开展网格化自适应测点规划研究。将复杂曲面模型转化成细粒度的三角网格模型；进而采用三角网格边简化方法进行自适应测点规划。利用局部多项式拟合和局部曲率估算技术，实现网格顶点的自适应精简；通过顶点替代法，避免网格化离散误差的影响；采用子集选择技术

提升简化效率。实验结果表明：该方法不会引入网格化离散误差，对网格化粒度不敏感；在同样测点的情况下，最大误差较均匀采样法减小32.8%，较随机Hammersely序列法减小16.9%，均值误差则分别减小28.7%，18.5%。通过网格化能避免多张曲面间的协调处理困难问题；规划的测点能较好地反映曲面的加工质量。

Abstract

Layout optimization of inspection points is key for the inspection of geometric errors in models with complex surfaces. To deal with difficulties in the adaptive planning of whole inspection points of model components that were characterized by multiple surface characteristics

mesh-based adaptive planning of inspection points was studied. A complex surface model was transformed into a dense triangular mesh model

and the triangular mesh simplification method was used for adaptive planning of inspection points. The local polynomial fitting and local curvature estimation technology were used for adaptive reduction of mesh vertexes. The vertex substitution method was used to avoid any influence from the meshing discretization error. The subset selection technology was used to improve reduction efficiency. The experimental results show that this method should not introduce the meshing discretization error of the surface

and that it was not sensitive to meshing granularity. The maximal error of the mesh-based method described here should reduce by 32.8% under the same detection points in comparison to that of the uniform sampling method

and should reduce by 16.9% in comparison to that of the random Hammersely sequence method. The mean error of the mesh-based method should reduce by 28.7% and 18.5% in comparison to that of the uniform sampling method and the random Hammersely sequence method

respectively. Meshing can avoid coordination difficulties among multiple surfaces

and the planned detection points can objectively reflect the processing quality of the complex surface.

关键词

Keywords

references

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