Fitting margin projection of micro-drill based on Sanger algorithm with lateral connection

GE Dong-yuan; YAO Xi-fan; XIANG Wen-Jiang

doi:10.3788/OPE.20111903.0567

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Fitting margin projection of micro-drill based on Sanger algorithm with lateral connection

Article | 更新时间：2020-08-12

- Fitting margin projection of micro-drill based on Sanger algorithm with lateral connection
- Optics and Precision Engineering Vol. 19, Issue 3, Pages: 567-572(2011)
- 作者机构：
  
  1. 华南理工大学机械与汽车工程学院,广东广州 510640
  2. 邵阳学院机械与能源工程系,邵阳湖南 422004
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111903.0567
  CLC： TB92;TP391
- Received：05 May 2010，
  
  Revised：28 June 2010，
  
  Published Online：22 March 2011，
  
  Published：22 March 2011
- 稿件说明：
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葛动元, 姚锡凡, 向文江. 基于侧向连接Sanger算法实现微钻头棱边投影的拟合[J]. 光学精密工程, 2011,19(3): 567-572

GE Dong-yuan, YAO Xi-fan, XIANG Wen-Jiang. Fitting margin projection of micro-drill based on Sanger algorithm with lateral connection[J]. Editorial Office of Optics and Precision Engineering, 2011,19(3): 567-572
葛动元, 姚锡凡, 向文江. 基于侧向连接Sanger算法实现微钻头棱边投影的拟合[J]. 光学精密工程, 2011,19(3): 567-572 DOI： 10.3788/OPE.20111903.0567.

GE Dong-yuan, YAO Xi-fan, XIANG Wen-Jiang. Fitting margin projection of micro-drill based on Sanger algorithm with lateral connection[J]. Editorial Office of Optics and Precision Engineering, 2011,19(3): 567-572 DOI： 10.3788/OPE.20111903.0567.

摘要

针对微钻头的圆角、外径等的检测

研究了微钻头棱边投影的拟合方法。首先

采用印刷电路板(PCB)微钻头高精度自动化检测系统采集图像。在对微钻头棱边投影的椭圆方程进行拟合时

以采样点坐标的组合矢量坐标到超平面距离的平方和为目标函数。然后

根据求解目标

设计一个有侧向连接的Sanger网络

以采样点坐标组成的矢量坐标为Sanger网络的输入。最后

采用自适应次分量的提取方法

以自相关矩阵的最小特征值所对应的特征向量为超平面的拟合系数

即椭圆方程拟合系数

得到微钻头的圆角、外径等技术指标。这种自适应Sanger网络在工件形状误差检测中的应用方法能满足微钻头检测的精度要求。

Abstract

To measure the rounded corner and diameter of a micro-drill

the fitting of the elliptical equation for margin projection of the micro-drill was researched.Firstly

the margin projective image was collected with a high precise automatic test system of PCB micro-drill. While the elliptical equation of margin projection of micro-drill was fitted

the sum of square distance from the sample points vector coordinates to the hyperplane determined by the elliptical coefficients was taken as an objective function. Then

a Sanger neural network with lateral connection was designed

in which the input signal were vector coordinates composed of sample points.Finally

on the basis of an adaptive minor component extracting method

the eigenvector of minimum eigen values was taken as the fitted coefficients of the hyperplane

i.e.

fitted elliptical coefficients

and the rounded corner and diameter of the micro-drill were obtained. The proposed approach can meet the precision requirements of micro-drill testing

and is a novel application of adaptive Sanger network to measuring shape errors.

关键词

Keywords

references

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