Abstract
This research presents a camera-based measurement system which is developed to improve the safety and reliability for gear profile measurement system. Gear profile measurement is vital in precision engineering. To increase the safety and reliability of the precision measurement, application of camera or vision is very useful. Automatic control is also necessary to increase reliability of the measurement system. Normally, gear profiles are measured using contact-based stylus system. During gear profile measurement, human monitoring is required to avoid accident and sometimes we may face great danger regarding safety of our body especially eyes. The stylus is sharp and thin and if it is collided to the gear teeth there is high probability of breaking and scattering the stylus tip. To save time, if the measurement probe scans the gear shape with a speed of 10 mm/s then the issue of safety should be considered highly. The traditional methods for gear measurement are either time consuming or expensive. This paper presents the successful implementation of the camera system in precision measurement which saves time and increases safety and reliability of the measurement with the increment of the measurement performance by increasing production rate. Color-based stylus tracking algorithm is implemented to acquire better reliability of the complete system. Thus, the developed system with vision enhances safety and reliability of the precision measurement.
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Ali, MD. H., Kurokawa, S., Uesugi, K.: Vision based measurement system for gear profile. In: IEEE International Conference of Informatics, Electronics and Vision (2013) doi:10.1109/ICIEV.2013.6572652
Marciniec, A., Budzik, G., Dziubek, T.: Automated Measurement of Bevel Gears of the air craft gearbox using GOM. J. KONES Power Train Transp. 18(2) 259–264 (2011)
Tian, G.Y., Lu, R.S., Gledhill, D.: Surface measurement using active vision and light scattering. Opt. Lasers Eng. 45(1), 131–139 (2007)
Al-Kindi, G.A., Shirinzadeh, B.: An evaluation of surface roughness parameters measurement using vision-based data. Int. J. Mach. Tools Manuf. 47(3–4), 697–708 (2007)
Jeyapoovan, T., Murugan, M.: Surface roughness classification using image processing. Measurement 46(7), 2065–2072 (2013)
Su, J.C., Huang, C.K., Tarng, Y.S.: An automated flank wear measurement of microdrills using machine vision. J. Mater. Process. Technol. 180(1—-3), 328–335 (2006). ISSN 0924–0136
Ting-Fa, X., Peng, Z.: Precise perimeter measurement for 3D object with a light-pen vision measurement system. Opt. Laser Technol. 41(6), 815–819 (2009). ISSN 0030–3992
Withrobot Lab. http://www.withrobot.com (2012)
Fukuda, Y., Feng, M.Q., Shinozuka, M.: Cost-effective vision-based system for monitoring dynamic response of civil engineering structures. Struct. Control Health Monit. 17(8), 918–936 (2010)
Lee, J.J., Shinozuka, M.: A vision-based system for remote sensing of bridge displacement. NDT Int. 39(5), 425–431 (2006)
Choi, H.S., Cheung, J.H., Kim, S.H., Ahn, J.H.: Structural dynamic displacement vision system using image processing. NDT E Int. 44(7), 597–608 (2011)
Jainy, S.: Machine vision based identification and dimensional measurement of electronic components. Master’s Thesis, p. 12 (2006)
Dalsa technology: Precision measurements with machine vision, USA. https://www.teledynedalsa.com
Muljowadidodo, K., Mohammad, A.R., SaptoAdi, N., Budiyono, A.: Vision based distance measurement system. Indian J. Mar. Sci. 38(3), 327 (2009)
Mohamed, A., Esa, A.H., Ayub, M.A.: Roundness measurement of cylindrical parts by machine vision. In: International Conference on Electrical, Control and Computer Engineering, pp. 486–490 (2011)
Zhang, T., Luo, Y., Wang, X., Wang, M.: Machine vision technology for measurement of miniature parts in narrow space using borescope. In: International Conference on Digital manufacturing and Automation (ICDMA), China, pp. 904–907 (2010)
Kondo, Y., Osawa, S., Sato, O., Komori, M., Takatsuji, T.: Evaluation of instruments for pitch measurement using a sphere artifact. Precis. Eng. 36(4), 604–611 (2012)
http://www.codeproject.com/Articles/31104/Lego-Pan-Tilt-Camera-and-Objects-Tracking
http://www.codeproject.com/Articles/8374/Tracking-an-object-from-a-live-video-input
Kurada, S., Bradley, C.: A review of machine vision sensors for tool condition monitoring. Comput. Ind. 34(1), 55–72 (1997)
http://www.codeproject.com/Articles/91470/Computer-Vision-Laser-Range-Finder
https://workspaces.codeproject.com/shellscript/computer-vision-laser-range-finder/article/
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Ali, M.H., Kurokawa, S. & Uesugi, K. Application of machine vision in improving safety and reliability for gear profile measurement. Machine Vision and Applications 25, 1549–1559 (2014). https://doi.org/10.1007/s00138-014-0619-0
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DOI: https://doi.org/10.1007/s00138-014-0619-0