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Title:Detection system of forging position and ejector based on machine vision
Authors: Ling Yunhan1 Shao Guangbao2 Sun Yong1 Jiang Peng1 Yao Hongliang1 Su Zining1 
Unit: (1.Beijing Research Institute of Mechanical & Electrical Technology Beijing 100083 China 2.Hubei Tri-Ring Forging Co. Ltd. Gucheng 441700 China) 
KeyWords: machine vision  forging automation  industrial camera  position detection  ejector detection 
ClassificationCode:TP23
year,vol(issue):pagenumber:2018,43(5):0-0
Abstract:

 At present, most of forging automation production lines in China are restricted by the risk factors that sticking and ejector cannot be recovered during the forging process, and it is often necessary to manually judge whether the workpiece position satisfies the continuous processing conditions before machining. To solve this problem, a forging location detection system based on machine vision was proposed, and the industrial CCD camera was used to replace the human eye to determine whether the workpiece position met the requirements of plastic grasping for robot grabbing or pressing machine. Then, the hardware composition, detection principle and detection algorithm of the detection system were described, and a method for detecting whether the hydraulic ejector bar could be recovered without rigid connections designed. The experimental results show that the single detection time of the detection system is less than 500 ms which has no missing result, and the error rate is less than 2%. Furthermore, the causes of false results were analyzed. And the system is of high detection speed and high rate of accuracy. Finally, by applying the above system, the number of detection operators reduces 2-3.

Funds:
2015年智能制造新模式应用(工业和信息化部[2015]354号)
AuthorIntro:
作者简介:凌云汉(1990-),男,硕士研究生 Email:424212121@qq.com 通讯作者:孙勇(1971-),男,博士,研究员 Email:sun_yong_89@163.com
Reference:

 
[1]陈裕潮,蔡念,刘根,等. 一种基于机器视觉的轮胎模具表面字符检测方法
[J]. 锻压技术,2016,41(12):127-130.


Chen Y C, Cai N, Liu G,et al. A character inspection method on tire mould surface based on machine vision
[J]. Forging & Stamping Technology, 2016,41(12):127-130.


[2]阎镭,梁冬泰,向桂山,等. 机器视觉在自动化生产线状态检测与故障诊断中的应用
[J]. 液压与气动,2006,(12):65-68.
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