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Tool Monitoring System using Vision System with Minimizing External Condition  

Kim, Sun-Ho (동의대학교 메카트로닉스공학과)
Baek, Woon-Bo (동의대학교 메카트로닉스공학과)
Publication Information
Journal of the Korean Society of Manufacturing Process Engineers / v.11, no.5, 2012 , pp. 142-147 More about this Journal
Abstract
Machining tool conditions directly affect to quality of product and productivity of manufacturing. Many researches performed for tool condition monitoring in machining process to improve quality and productivity. Conventional methods use characteristics of signal for cutting force, motor current consumption, vibration of machine tools and machining sound. Recently, diameter of machining tool is become smaller for minimizing of mechanical parts. Tool condition monitoring using conventional methods are relatively difficult because micro machining using small diameter tool has low machining load and high cutting speed. These days, the direct monitoring for tool conditions using vision system is performed actively. But, vision system is affected by external conditions such as back ground of image and illumination. In this study, minimizing technology of external conditions using distribution analysis of image data are developed in micro machining using small diameter drill and tap. The image data is gathered from vision system. Several sets of experiment results are performed to verify the characteristics of the proposed machining technology.
Keywords
Tool Monitoring System; Vision System; Tap; Drill;
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  • Reference
1 Kim, W. S. and Kim, D. H., "An Experimental Study on the Detection of Tool Failure in Face Milling Processes", J. of KSMTE, Vol. 5, No. 3, pp. 73-79, 1996.
2 Kim, G. D. and Chu, C. N., "Prediction of the Amount of Tool Fracture in Face Milling using Cutting Force Signal", J. of KSME, Vol. 25, pp. 972-979, 2001.
3 Lee, J. M. and Huh, I. K. "Tool Breakage Monitoring by Feed Motor Current during Milling Process", J. of KSPE, Vol. 12, No. 3, pp. 63-72, 1995.
4 Kwon, O. D. and Yang, M. Y., "Tool Condition Monitoring Technique using Computer Vision and Pattern Recognition", J. of KSME, Vol. 17, pp. 27-37, 1993.
5 Lee, C. H. and Cho, T. D., "A Study on the End Mill Wear Detection by the Pattern Recognition Method in the Machine Vision", J. of KSPE, Vol. 20, No. 4, pp. 223-229, 2003.
6 Kang, I. S., Jeong, Y. S., Kwan, D. H., Kim, J. H., Kim, J. S. and Ahn, J. H., "Tool Condition Monitoring using AE Signal in Micro End Milling", J. of KSPE, Vol. 23, No. 1, pp. 64-71, 2006.