Intelligent Vision Methodology for Detection of the Cutting Tool Breakage
Author(s) -
Abdallah A. Alshennawy,
Ayman A. Aly
Publication year - 2013
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2013.06.06
Subject(s) - computer science , artificial neural network , chain code , artificial intelligence , breakage , fuzzy logic , feature (linguistics) , machine vision , feature extraction , pattern recognition (psychology) , computer vision , image (mathematics) , world wide web , linguistics , philosophy
In this paper, a new Intelligent system based on neurofuzzy for detecting and diagnostics the wear and damage of the milling cutter is presented. The compatibility between the computer vision and neurofuzzy techniques is introduced. The proposed approaches consists of capturing the milling cutter image, Fuzzy edge detection, Chain code technique for feature extraction and finally, apply the neural network on the feature. The results of the study are three different diagnostics models, The first is diagnostic model for the original profile of the perfect cutter, the second is model for the wearied profile and the third is model for the damage profile. Experimental test results show that the proposed system is reliable, practical and can be used for the easy distinguish between the wear and damage automatically
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