Abdallah A. Alshennawy

Work place: Design and prod. Eng. Dept. , Faculty of Engineering, Tanta University, Egypt



Research Interests: 2D Computer Graphics, Computer Graphics and Visualization, Computer Vision


Dr. AbdallAh A. Alshennawy was Born in El Mansoura -Egypt, at 1968-03-10, B.Sc. 1991 and M.Sc. in Computer Vision of Two Dimensional Measurement and Inspection from Prod. And Design Eng. Dept., El Mansoura University, Egypt, 1995 and PhD. in Computer Vision of Three Dimensional Measurement and Inspection from Prod. And Design Eng. Dept., El Mansoura University, Egypt, 2003. Nowadays, he is a Lecturer at the Production and Design Engineering dept., Faculty of Engineering, Tanta University, Egypt

Author Articles
Self Learning Intelligent Controller of Electro hydraulic Actuator

By Ayman A.Aly Abdallah A. Alshennawy A.Abo-Ismail S.Dossokey

DOI: https://doi.org/10.5815/ijem.2013.01.03, Pub. Date: 29 Jun. 2013

The use of electro-hydraulic cylinders in industry has been becoming increasingly popular. A Fuzzy Logic Controller (FLC), which consists of the linguistic defined fuzzy sets and the control rules, is designed to control of the electro-hydraulic cylinder. Using the triangle shaped membership function; the position of the servo cylinder was successfully controlled. When the system working condition is altered, the control algorithm is shown to be more robust compared to the PID controller.

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Intelligent Vision Methodology for Detection of the Cutting Tool Breakage

By Abdallah A. Alshennawy Ayman A. Aly

DOI: https://doi.org/10.5815/ijitcs.2013.06.06, Pub. Date: 8 May 2013

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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Other Articles