Abdallah A. Alshennawy; Ayman A. Aly

Intelligent Vision Methodology for Detection of the Cutting Tool Breakage

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Author(s)

Abdallah A. Alshennawy ^1,* Ayman A. Aly ^2,3

1. Design and prod. Eng. Dept. Tanta University, Egypt

2. Mechatronics Sec. Dept. of Mechanical Engineering, Faculty of Engineering, Assiut University, 71516, Assiut, Egypt

3. Mechatronics Sec. Dept. of Mechanical Engineering, Faculty of Engineering, Taif University, 888, Taif, Saudi Arabia

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2013.06.06

Received: 3 Sep. 2012 / Revised: 20 Jan. 2013 / Accepted: 12 Mar. 2013 / Published: 8 May 2013

Index Terms

Intelligent Vision, Parts Classification, Chain Code, Diagnostics, Fuzzy Logic, Neural Networks

Abstract

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.

Cite This Paper

Abdallah A. Alshennawy, Ayman A. Aly, "Intelligent Vision Methodology for Detection of the Cutting Tool Breakage", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.6, pp.41-49, 2013. DOI:10.5815/ijitcs.2013.06.06

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International Journal of Information Technology and Computer Science (IJITCS)