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A Study on the Estimation of the Flat Zone Length by using Image Processing  

Roh, Dae-Ho (경희대학교 기계공학과)
Park, Hwan-Seo (경희대학교 기계공학과)
Lee, Hong-Guk (경희대학교 기계공학과)
Shin, Kwan-Soo (인천대학교 기계시스템공학부)
Yoo, Song-Min (경희대학교 기계공학과)
Publication Information
Journal of the Korean Society of Manufacturing Technology Engineers / v.19, no.5, 2010 , pp. 672-677 More about this Journal
Abstract
The goal of this study is to simplify the measurement process of the flat zone length produced by a flexible disk grinding system for the process automation. The image of workpiece in the grinding process is obtained, and the cutting speed and the feeding speed are controlled carefully to maximize the flat zone length. The gradient, the inflection point and the length of the line in the image are calculated, and the length is also measured by using a projector. Processing conditions and inversely proportional to flat zone length was changing. The flat zone length is estimated by Neural network algorithm considering the process conditions with the estimated error range as 0.06~3.61%, the Neural network algorithm for the grinding process estimation is found to be useful for building the process automation database.
Keywords
Disk grinding; Flat zone; Processing condition; Projector; Neural network;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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