A GUI Software for Automatic Assembly Based on Machine Vision

2018 ◽  
Author(s):  
Hao-dong Chen ◽  
Yi-fan Wang ◽  
Zheng Guo ◽  
Wen-xiu Chen ◽  
Ping Zhao
Keyword(s):  
Machine Vision ◽  
Automatic Assembly

scholarly journals Using Machine Vision for Flexible Automatic Assembly System

2016 ◽  
Vol 96 ◽  
pp. 428-435 ◽  
Author(s):  
Phansak Nerakae ◽  
Pichitra Uangpairoj ◽  
Kontorn Chamniprasart
Keyword(s):  
Machine Vision ◽  
Assembly System ◽  
Automatic Assembly

The Application of Machine Vision in Automatic Assembly of Locks

2013 ◽  
Vol 646 ◽  
pp. 158-163
Author(s):  
Qing Min Liu ◽  
Cheng Zhang Gu ◽  
Zhi Kui Liu ◽  
Ling Zhao
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Production Efficiency ◽  
Assembly System ◽  
Automatic Assembly ◽  
Time Performance ◽  
System Requirements ◽  
The Difference ◽  
Assembly Precision

In the automatic assembly of locks system the pins’ selection depends on depth of key’s groove. Although the kinds of groove’s depth are fixed, the arrangements are random and they can’t be unpredictable. The difference in depth of key’s groove is very small, so it can’t be judged by eyes accurately. To solve the problem that the pins assembly is tried frequently, the depth of keys’ groove can be measured accurately by the machine vision. So the problem of the serious influence production efficiency is solved successfully. This kind lock is widely used and machine’s cost is very low by allocation. The experiments show that this method fully met the locks automatic assembly system requirements from the assembly precision, real time performance and robustness and other aspects, solving the problems encountered in the lock assembly.

Integrity Detection of Automatic Assembly for Lamp Parts Based on Color and Shape Feature

2014 ◽  
Vol 1030-1032 ◽  
pp. 1721-1725
Author(s):  
Pei Pei Wu ◽  
Ping An Mu ◽  
Shu Guang Dai
Keyword(s):  
Quality Control ◽  
Machine Vision ◽  
Industrial Production ◽  
Template Matching ◽  
Automatic Assembly ◽  
Shape Feature ◽  
Color Feature ◽  
Material Resources ◽  
Parts Manufacturing

In industrial production, the machine vision save a lot of manpower and material resources. And it has become an indispensable part of quality control solutions in automobile and parts manufacturing. In order to detect the integrity of automatic assembly for lamp parts, we first use the shape feature to determine whether the part shape is right through egde detection and template matching algorithms. And if the shape is right, we can further detect the color feature which are different in different sales regions using the color moments. As a result, the missing and mistake packing can be detected.

Micro-Stress Assembly of Fragile Miniature Parts

2011 ◽  
Vol 483 ◽  
pp. 668-673
Author(s):  
Xiao Dong Wang ◽  
Lin Wang ◽  
Xi Wen Zhang ◽  
Yi Luo ◽  
Li Ping Liu
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Machine Vision ◽  
Influencing Factors ◽  
Force Feedback ◽  
Assembly System ◽  
Automatic Assembly ◽  
Compliant Structure ◽  
New Type ◽  
And Control

Since miniature parts have the characteristics of small sizes, low strength and rigidity, and they are easily to be damaged during the process of assembly, a concept for micro-stress assembly was proposed. In order to achieve micro-stress assembly, an automatic assembly system based on machine vision and force feedback was developed. Finite element method was used to analyze the influencing factors causing assembly stress. In order to handle various kinds of parts, a new type of combined gripper was developed, furthermore, the gripper integrated with force feedback and a compliant structure can detect and control the manipulating force.

Machine Vision

2009 ◽  
Author(s):  
Wesley E. Snyder ◽  
Hairong Qi
Keyword(s):  
Machine Vision

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

Machine Vision, Let's Go into the Street

1997 ◽  
Vol 117 (10) ◽  
pp. 1339-1344
Author(s):  
Katsuhiko Sakaue ◽  
Hiroyasu Koshimizu
Keyword(s):  
Machine Vision

Machine Vision Technologies to Connect with Humans

2005 ◽  
Vol 125 (11) ◽  
pp. 692-695
Author(s):  
Kazunori UMEDA ◽  
Yoshimitsu AOKI
Keyword(s):  
Machine Vision
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