吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (4): 1076-1080.doi: 10.13229/j.cnki.jdxbgxb201404027

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Vision inspection technology of fracture splitting notch of auto connecting rod

LIU Chang-ying1, CAI Wen-jing1, WANG Tian-hao2, LI Ji-zhi1, JIA Yan-mei1, SONG Yu-he1   

  1. 1.College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China;
    2.College of Automotive Engineering, Jilin University, Changchun 130022, China
  • Received:2013-01-19 Online:2014-07-01 Published:2014-07-01

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Abstract: In traditional manual detection of fracture splitting notch of auto connecting rod, the workload is heavy, the efficiency is low and the detecting error is big. To overcome these shortcomings, an improved machine vision inspection method is proposed. This method uses a CCD camera to obtain detection image, and filters out the background noise by homomorphic filtering technique to improve the quality of the detected images. It uses the self-adaptive threshold Canny edge detection method to extract the edge information. The target feature is recognized and judged by measuring its circularity and oblateness. The proposed method is verified by auto connecting rod detection experiment. Results show that using the proposed method can realize quick and accurate detection of auto connecting rod.

Key words: automatic technology, auto connecting rod, machine vision, homomorphic filtering, edge operator

CLC Number: 

  • TP247.5
[1] 寇淑清, 王金伟, 郑祺峰, 等. 曲轴轴承座/连杆激光加工裂解槽的组织与胀断性能[J].光学精密工程, 2011, 19(4):768-774. Kou Shu-qing, Wang Jin-wei, Zheng Qi-feng, et al. Organization and expansion breaking performance of fracture notch of crankshaft breaking and connecting rod by laser processing[J].Optics and Precision Engineering, 2011, 19(4):768-774.
[2] Tian Yuan-yuan, Liu Si-yang, Tan Qing-chang. Application of detecting part's size online based on machine vision[J]. Energy Procedia, 2012, 16: 1948-1956.
[3] 李喆, 费敏锐, 周文举. 基于机器视觉的瓶盖表面检测技术的研究[J].仪表技术, 2012(9):31-34. Li Zhe, Fei Min-rui, Zhou Wen-ju. Reserch of cap surface inspection technology based on machine vision[J]. Instrumentation Technology, 2012(9): 31-34.
[4] Urbanek J, Barszcz T, Uhl T, et al. Leak detection in gas pipelines using wavelet-based filtering[J]. Structural Health Monitoring, 2012, 11:405-412.
[5] Yang W D, Guo W, Peng K, et al. Research on removing shadow in workpiece image based on homomorphic filtering[J]. Procedia Engineering, 2012, 29:2360-2394.
[6] 王宣银, 梁冬泰. 基于多元图像分析的表面缺陷检测算法[J].浙江大学学报:工学版, 2010, 44(3): 448-452. Wang Xuan-yin, Liang Dong-tai. Surface defect detection based on multivariate image analysis[J]. Journal of Zhejiang University (Engineering Science), 2010, 44(3):448-452.
[7] Zhao X M, Wang W X, Wang L P. Parameter optimal determination for Canny edge detection[J]. Imaging Science Journal, 2011, 59(6):332-341.
[8] 唐路路, 张启灿, 胡松. 一种自适应阈值的Canny边缘检测算法[J]. 光电工程, 2011(5):127-132. Tang Lu-lu, Zhang Qi-can, Hu Song. An improved algorithm for Canny edge detection with adaptive threshold[J]. Opto-Electronic Engineerig, 2011(5):127-132.
[9] Han Ping, Wu Jing-xian, Wu Ren-biao. SAR target feature extraction and recognition based on 2D-DLPP[J]. Physics Procedia, 2012, 24:1431-1436.
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