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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/10280

Title: Classifying surface roughness for turning process with neural network
Authors: Roshaliza, Hamidon
Tang, Sai Hong, Dr.
Suhaila, Hussain
Mohd Fathullah, Ghazali
???metadata.dc.contributor.url???: roshaliza@unimap.edu.my
saihong@eng.upm.edu.my
suhaila@unimap.edu.my
fathullah@unimap.edu.my
Keywords: Surface roughness;Machine vision;Discrete Cosine Transformation (DCT);SOM neural network;Regional Conference on Applied and Engineering Mathematics (RCAEM)
Issue Date: 2-Jun-2010
Publisher: Universiti Malaysia Perlis (UniMAP)
???metadata.dc.publisher.department???: Institut Matematik Kejuruteraan
Citation: Vol.1(31), p.179-182
Series/Report no.: Proceedings of the 1st Regional Conference on Applied and Engineering Mathematics (RCAEM-I) 2010
Abstract: using stylus measurement technique. The drawbacks of this technique are the contact between the stylus tip and the measured surface will produce scratches and the measuring speed is slow. A new system for controlling surface quality for turning process has been developed that applies the concept of machine vision technique. It uses a DCT (Discrete Cosine Transformation) technique for image processing and Self Organizing Map (SOM) as learning architecture in neural network. This system is able to classify the surface roughness of turning part into “WORN” and “UNWORN” category
Description: 1st Regional Conference on Applied and Engineering Mathematics (RCAEM-I) 2010 organized by Universiti Malaysia Perlis (UniMAP) and co-organized by Universiti Sains Malaysia (USM) & Universiti Kebangsaan Malaysia (UKM), 2nd - 3rd June 2010 at Eastern & Oriental Hotel, Penang.
URI: http://hdl.handle.net/123456789/10280
Appears in Collections:Conference Papers

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