微薄硅晶片高速视觉定位及矫正系统

张美杰; 张平

doi:10.12052/gdutxb.170077

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微薄硅晶片高速视觉定位及矫正系统

综合研究 | 更新时间：2026-05-27

- 微薄硅晶片高速视觉定位及矫正系统
- High-speed Visual Positioning and Correction System of Thin Silicon Wafer
- 广东工业大学学报 2018年34卷第1期页码：9-15
- 作者机构：
  
  1. 广东工业大学　机电工程学院,广东,广州,510006
  2. 佛山广工大数控装备研究院,广东,佛山,528225
- 作者简介：
  
  张美杰(1992–)，男，硕士研究生，主要研究方向为图像处理与模式识别
  张平(1965–)，男，教授，博士，主要研究方向为精密数字化装备、高速高精数控系统. E-mail：p-zhang@126.com
- 基金信息：
- DOI：10.12052/gdutxb.170077
  中图分类号： TP391
- 网络首发：2018-01-09，
  
  纸质出版：2018
- 稿件说明：
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张美杰, 张平. 微薄硅晶片高速视觉定位及矫正系统[J]. 广东工业大学学报, 2018, 34(1): 9-15.

Zhang Mei-jie, Zhang Ping. High-speed Visual Positioning and Correction System of Thin Silicon Wafer[J]. 2018, 34(1): 9-15.
张美杰, 张平. 微薄硅晶片高速视觉定位及矫正系统[J]. 广东工业大学学报, 2018, 34(1): 9-15. DOI： 10.12052/gdutxb.170077.

Zhang Mei-jie, Zhang Ping. High-speed Visual Positioning and Correction System of Thin Silicon Wafer[J]. 2018, 34(1): 9-15. DOI： 10.12052/gdutxb.170077.

摘要

为解决当前机械定位存在的不足

提出了一种微薄硅晶片高速视觉定位及矫正系统. 视觉定位算法采用链码跟踪以及Principal Component Analysis(PCA)获得“主元”

在此基础上采用线段聚类的直线检测算法

拟合出电池片的边缘直线；然后计算出电池片的位置和角度偏差

通过机械手进行位置和角度矫正. 实验结果验证了该系统算法的实用性. 在实际生产中

该系统能够快速、精确地对电池片进行定位和矫正

大大增加了电池片串焊的效率和精度.

Abstract

In order to solve the disadvantages of the current mechanical positioning

a high speed vision positioning and correction system for a thin silicon wafer is proposed. The visual location algorithm gets the "master yuan" using the chain code tracking and Principal Component Analysis (PCA)

on the basis of the line detection algorithm of line segment clustering

the edge line of the cell is fitted

and then the cell position and angle deviation are calculated

and finally

position and angle are corrected by using manipulator. The experimental results verify the practicability of the algorithm. In the actual production

the system can quickly and accurately locate and correct the battery

greatly increasing the efficiency and accuracy of the battery string welding.

关键词

Keywords

references

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DAI Z S, PAN Q, CHANG, G L, etc. Machine vision chip pin welding defect detection based on [J]. Journal of Guangdong University of Technology, 2016, 33 (3): 65-69.

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