|本期目录/Table of Contents|

[1]黄正文,陈宁.零件的机器视觉自动识别检测系统[J].集美大学学报(自然科学版),2017,22(2):48-56.
 HUANG Zhengwen,CHEN Ning.Design on Parts'Automatic Detection and Identification System on Machine Vision[J].Journal of Jimei University,2017,22(2):48-56.
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零件的机器视觉自动识别检测系统(PDF)
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《集美大学学报(自然科学版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第22卷
期数:
2017年第2期
页码:
48-56
栏目:
船舶与机械工程
出版日期:
2017-03-28

文章信息/Info

Title:
Design on Parts'Automatic Detection and Identification System on Machine Vision
作者:
黄正文陈宁
(集美大学机械与能源工程学院 ,福建 厦门 361021)
Author(s):
HUANG ZhengwenCHEN Ning
(School of Mechanical and Energy Engineering,Jimei University,Xiamen 361021,China )
关键词:
零件机器视觉检测识别自动系统
Keywords:
partsmachine visiondetection and identificationautomatic system
分类号:
-
DOI:
-
文献标志码:
A
摘要:
为了实现零件识别检测的自动化与零件生产的智能化,将机器视觉与运动控制理论结合,采用脉冲耦合式神经网络PCNN(pulse coupled neural network)边缘检测识别的方法,初步设计出一套机器视觉自动识别检测系统,对继电器盖等小型零件进行了检测识别实验。实验结果表明,该视觉检测识别自动化系统改善了零件检测自动化程度,提高了尺寸精度,优化了系统鲁棒性,最终实现了对零件实时筛选分类与零件的高效率生产。
Abstract:
In order to realize the automatic detection and identification of parts and intelligentize the manufacturing process,a preliminary design for automatic detection and identification system based on pulse coupled neural network (PCNN) is put forward by combining machine vision and motion control theory.Corresponding experiments for relay cover have been carried out.It shows that the proposed system can increase the level of automatic detection.And it also reveals that the size precision of parts and the robustness of the system have been improved.Conclusion are drawn that the system can classify the parts in real time and in high productivity.

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更新日期/Last Update: 2017-05-19