Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/75032
Title: Machine vision monitoring of tool wear
Authors: Wong, Y.S. 
Yuen, W.K.
Lee, K.S. 
Bradley, C. 
Issue Date: 1998
Citation: Wong, Y.S.,Yuen, W.K.,Lee, K.S.,Bradley, C. (1998). Machine vision monitoring of tool wear. Proceedings of SPIE - The International Society for Optical Engineering 3518 : 17-24. ScholarBank@NUS Repository.
Abstract: Automated tool condition monitoring is an enabling technology in the push to develop fully unmanned machining centers. If this goal can be achieved across a broad range of machine tools, then researchers have assisted industry in moving one step closer to attaining truly flexible manufacturing work cells. Recent advances in the field of image processing technology have led to experimentation with machine vision as a potential means of directly evaluating tool condition. In this work, a machine vision system is employed that permits direct milling insert wear measurement to be accomplished in-cycle. The system is characterized by measurement flexibility, good spatial resolution and high accuracy. The flank wear monitoring system consists of an illumination source, CCD camera and high-resolution microscope lens. The extent of flank wear on the milling inserts was measured using the vision system and an image-processing algorithm. Two vision-based parameters were developed and their efficacy in directly quantifying insert flank wear was compared with measurements on a traditional toolmaker's microscope.
Source Title: Proceedings of SPIE - The International Society for Optical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/75032
ISSN: 0277786X
Appears in Collections:Staff Publications

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