Vision based intelligent recognition and assembly guidance of aerospace electrical connectors

被引：0
作者：
Wang J. [1 ]
Wang L. [2 ]
Fan X. [1 ]
Yin X. [1 ]
机构：
[1] Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai
[2] Shanghai Spaceflight Precision Machinery Institute, Shanghai
来源：
Fan, Xiumin (xmfan@sjtu.edu.cn) | 2017年 / CIMS卷 / 23期
关键词：
Aerospace electrical connection; Hough transformation; Image feature extraction; Intelligent guidance; Part recognition; Support vector machine;
D O I：
10.13196/j.cims.2017.11.011
中图分类号：
学科分类号：
摘要：
To improve the manual assembly efficiency of aerospace products, a visual-based intelligent recognition and assembly guide method of aerospace electrical connectors was proposed. The area of parts in the original image was extracted with skin color feature and contour feature of electrical connector. The feature of electrical connector and SIFT feature were extracted into support vector machine classifier training to get the part training model. With Hough Transform (HT) and part training model, the on-line classification and identification of electrical connectors were realized. The whole process was automated. Through the pre-construction of three-dimensional assembly process information model, the corresponding parts of assembly process information was triggered and retrieved with identification results in real time to guide the assembly. The test result of the proposed method proved that the average accuracy rate of part recognition was more than 90% and the recognition time of each image were in two seconds, which could meet the requirements of identification accuracy and efficiency. © 2017, Editorial Department of CIMS. All right reserved.
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页码：2423 / 2430
页数：7
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