Abstract
According to the in-line inspection requirements of the surface mounted IC (integrated circuit) devices on the printed circuit board (PCB), an inspection algorithm based on the lead’s features was presented. Firstly, the features of the IC devices with different mounted quality under three colors (red, greed, blue) structure light source were analyzed. Secondly, the lead edge points were extracted with the first color derivative. Then the points were projected to avoid the difficulty of right thresholding. Based on the projections of the edges, the horizontal and vertical borders of the IC leads were obtained by the sliding location window algorithm. After location the leads, the defects such as missing devices, wrong devices, shifts and skews were inspected. Experiments results, from comparing with three existing method, show that our method possesses better performances both on efficiency and speed.
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References
Kim, T.H., Tho, T.H., Moon, Y.S.: Visual inspection system for the classification of solder joints. Pattern Recognition 32(4), 565–575 (1999)
Giaquinto, A., Fornarelli, G., Brunetti, G., Giaquinto, A.: A fuzzy method for globalquality index evaluation of solder joints in surface mount technology. IEEE Trans. Ind. Inf. 7, 115–124 (2011)
Wu, F.P., Zhang, X.M.: An Inspection and Classification Method for Chip Solder Joints Using Color Grads and Boolean Rules. Robotics and Computer-Integrated Manufacturing 30(5), 517–526 (2014)
Acciani, G., Brunetti, G., Chiarantoni, E.: An automatic method to detect missing devices in manufactured products. In: Proceedings of International Joint Conference on Neural Networks, pp. 2324–2329 (2004)
Liu, J.Q., Kuang, H., Ding, S.H.: Research on machine vision system for inspection of SMT chip pins. China Mechanical Engineering 18(16), 1908–1912 (2007)
Wu, H.H., Zhang, X.M., Kuang, Y.C.: Automated Visual Inspection of Surface Mounted Chip Components. In: IEEE International Conference on Mechatronics and Automation, pp. 189–1794 (2010)
Michael, E.Z., Stefanos, K.G., George, A.R.: A Bayesian framework for multilead SMD post-placement quality inspection. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 34(1), 440–453 (2004)
Xian, F.: Testing technology development promoted by HDI packaging technology. Equipment for Electronics Manufacturing 157, 32–35 (2008) (in Chinese)
Teoh, E.K., Mital, D.P., Lee, B.W., Wee, L.K.: Automated visual inspection of surface mount PCBs. In: IECON, 16th Annual Conference of IEEE, pp. 27–30 (1990)
Gallegos, J.M., Villalobos, J.R., Carrillo, G.: Reduced-dimension and wavelet processing of SMD images for real-time inspection. In: Proceeding of the IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 30–35 (1996)
Lu, S.L., Zhang, X.M., Kuang, Y.C.: Optimal illuminator design for automatic optical inspection systems. International Journal of Computer Applications in Technology 37(2), 101–108 (2010)
Cripin, A.J., Rankov, V.: Automated inspection of PCB components using a genetic algorithm template-matching approach. Int. J. Adv. Manuf. Technol. 35, 293–300 (2007)
Steger, C., Urich, M., Wideemamm, C.: Machine vision algorithms and applications, pp. 209–216. Publishing Tsinghua university, Beijing (2011) (in Chinese)
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Hui-hui, W., Sheng-lin, L. (2014). Research on Surface Mounted IC Devices Inspection Based on Lead’s Features*. In: Zhang, X., Liu, H., Chen, Z., Wang, N. (eds) Intelligent Robotics and Applications. ICIRA 2014. Lecture Notes in Computer Science(), vol 8918. Springer, Cham. https://doi.org/10.1007/978-3-319-13963-0_21
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DOI: https://doi.org/10.1007/978-3-319-13963-0_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13962-3
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