Title :
Failure detection and classification of circular sheets through the methods of perceptron neural network, Lvq and neurofuzzy using matlab and fuzzytech software
Author :
Iraji, Mohammad Saber ; Jahromi, Abdol Hamid Eshragh ; Tosinia, Azam
Author_Institution :
Dept. of Comput. Eng., Islamic Azad Univ., Gorgan, Iran
Abstract :
In this article, I have tried to design an intelligent system which can separate and classify perfect and defective circular plates according to their size. After preprocessing, specifications of defects and size are determined through image processing, and finally, a system is proposed through perceptron neural networks methods, neuro fuzzy method, and Lvq to separate these products on basis of their size and defects. In the designing of this system, when input and its related intend is obvious before training network, perceptron neural networks give more exact results. If input and its related output have been clarified but the output have been related to some sub-inputs, lvq method is used; and finally, when input and its related output have been mace clear but value of input variables is continuous, neuro fuzzy method is used.
Keywords :
failure analysis; fuzzy neural nets; image processing; perceptrons; Matlab; circular sheet; defective circular plate; failure detection; fuzzytech software; image processing; intelligent system; neuro fuzzy method; perceptron neural network; Computers; Image processing; Neurons; Pixel; Pragmatics; Support vector machine classification; Training; image processing; industrial automation; neural network; neuro fuzzy; products classification; specification of defect;
Conference_Titel :
Intelligent and Advanced Systems (ICIAS), 2010 International Conference on
Conference_Location :
Kuala Lumpur, Malaysia
Print_ISBN :
978-1-4244-6623-8
DOI :
10.1109/ICIAS.2010.5716170