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Advanced Automated Visual Inspection System of Colored Wires in Electric Cables

Authors(6):

Syed Sultan Mahmood, C. Altaf, V. Shiva Naga Malleswara Rao, M. Shashidhar, K. Manoj, R. Sriram Pranav
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In this paper, an automatic visual inspection system for checking the colored wires in electric cable is presented. The system is able to insert the cables wires through motors and rooting wires in correct block with the help of cable separator. This variability is managed in an automatic way by means of a learning subsystem which require to give manual input from the operator. once the model of a correct wire is rooted with sensor, it can automatically inspected to particular block.The main contributions of this paper are: color wire recognition is done with the help of color sensor. This work is motivated by the need of performing an accurate quality control an automated inspection method is necessary for effectively assuring a quality check on 80%. software system is composed by two main modules: the ?rst one localizes the wires from where to source the wire, while the second performs color detection where to root the wire. This paper explains how it is possible to recognize the wires in many different ways; moreover, a reliable method for identifying colors.

Syed Sultan Mahmood, C. Altaf, V. Shiva Naga Malleswara Rao, M. Shashidhar, K. Manoj, R. Sriram Pranav

Cable Feeder, Cable Separator, Arduino, Color Sensor, Interfacing ICs, Buzzer, Embedded C.

  1. T. Newman and A. Jain, "A survey of automated visual inspection," Compute. Vision Image Understanding, vol. 61, no. 2, pp. 231–262, 1995.
  2. E. Malamas, E. Petrakis, M. Zervakis, L. Petit, and J.-D.Legat,"A survey on industrial vision systems, applications and tools," Image Vision Comput., vol. 21, no. 2, pp. 171–188, 2003.
  3. M. Shirvaikar, "Trends in automated visual inspection," J. Real Time Image Process., vol. 1, no. 1, pp. 41–43, 2006.
  4. E. Guerra and J. Villalobos, "A three-dimensional automated visual inspection system for SMT assembly," Comput. Ind. Eng., vol. 40, no. 1, pp. 175–190, 2001.
  5. X. Lu, G. Liao, Z. Zha, Q. Xia, and T. Shi, "A novel approach for flip chip solder joint inspection based on pulsed phase thermography," NDT & E Int., vol. 44, no. 6, pp. 484–489, 2011.
  6. B. Suresh, R. Fundakowski, T. Levitt, and J. Overland, "A real-time automated visual inspection system for hot steel slabs," IEEE Trans. Pattern Anal. Mach. Intel., vol. 5, no. 6, pp. 563–572, Nov. 1983.
  7. G. Moreda, J. Ortiz-Cañavate, F. Garc´?a-Ramos, and M. Ruiz-Altisent, "Non-destructive technologies for fruit and vegetable size determination: A review," J. Food Eng., vol. 92, no. 2, pp. 119–136, May 2009.
  8. M. S. Millan and J. Escofet, "Fabric inspection by near-infrared machine vision," Opt. Lett., vol. 29, no. 13, pp. 1440–1442, July 2004.
  9. S. Ghidoni, M. Minella, L. Nanni, C. Ferrari, M. Moro, E. Pagello, and E. Menegatti, "Automatic crack detection in thermal images for metal parts," in Proc. Int. Conf. Heating by Electromagn. Sources, Padova, Italy, May 2013, pp. 181–188.
  10. T. Ummenhofer and J. Medgenberg, "On the use of infrared thermography for the analysis of fatigue damage processes in welded joints," Int. J. Fatigue, vol. 31, no. 1, pp. 130–137, 2009.
  11. C. Neubauer, "Intelligent x-ray inspection for quality control of solder joints," IEEE Trans. Compon. Packag. Manuf. Technol., Part C, vol. 20, no. 2, pp. 111–120, Apr. 1997.
  12. B. Jiang, C.-C. Wang, H.-J. Chen, and C.-C. Chu, "Automatic bubble defect inspection for microwave communication substrates using multi- threshold technique based co-occurrence matrix," Int. J. Prod. Res., vol. 48, no. 8, pp. 2361–2371, 2010.
  13. R. Ureña, F. Rodr´?guez, and M. Berenguel, "A machine vision system for seeds quality evaluation using fuzzy logic," Comput. Electron. Agriculture, vol. 32, no. 1, pp. 1–20, 2001.
  14. J. Jia, "A machine vision application for industrial assembly inspection," in Proc. IEEE 2nd Int. Conf. Mach. Vision, Dec. 2009, pp. 172–176.
  15. D. Shumin, L. Zhoufeng, and L. Chunlei, "Adaboost learning for fabric defect detection based on hog and SVM," in Proc. IEEE Int. Conf. Multimedia Technol. (ICMT), Jul. 2011, no. 1, pp. 2903–2906.

Publication Details

Published in : Volume 4 | Issue 7 | March-April - 2018
Date of Publication Print ISSN Online ISSN
2018-03-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
202-209 IJSRSET1844248   Technoscience Academy

Cite This Article

Syed Sultan Mahmood, C. Altaf, V. Shiva Naga Malleswara Rao, M. Shashidhar, K. Manoj, R. Sriram Pranav, "Advanced Automated Visual Inspection System of Colored Wires in Electric Cables ", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 7, pp.202-209, March-April-2018.
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