Experimantal & numeral study of temperature distribution during milling process in A537CL2 steel artivicial neural network alloy using
Publish place: 2nd International Conference on Management, Entrepreneurship and Economic Development
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
EME02_1761
تاریخ نمایه سازی: 14 شهریور 1393
Abstract:
Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects .In the present study the milling cross-section temperature is determined by using Artificial Neural Networks ( ANN ) according to the temperature of certain points of the work piece and the points specificallons and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer ( CHT ) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x , y , z and the milling rotational speed of the blade as input data to the network , the milling surface temperature determined by neural network is presented as output data . the desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN , CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process
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Authors
Mohammad Panahi
Department of mechanic Science and Research branch, Islamic Azad university, Kermanshah, Iran
Alireza Tahavvor
Department of mechanical Engineering, University of shiraz, Iran
Yaser Rezaie
Department of mechanic Science and Research branch, Islamic Azad university, shiraz, Iran