دانلود مقاله ISI انگلیسی شماره 52517
عنوان فارسی مقاله

پیش بینی دمای برش در ماشینکاری متعامد AISI 316L با استفاده از شبکه عصبی مصنوعی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
52517 2016 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Prediction of cutting temperature in orthogonal machining of AISI 316L using artificial neural network
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Soft Computing, Volume 38, January 2016, Pages 64–74

کلمات کلیدی
شبکه های عصبی مصنوعی - مدل المان محدود - درجه حرارت برش - برش متعامد - نیروهای برش
پیش نمایش مقاله
پیش نمایش مقاله پیش بینی دمای برش در ماشینکاری متعامد AISI 316L با استفاده از شبکه عصبی مصنوعی

چکیده انگلیسی

In this study, an approach based on artificial neural network (ANN) was proposed to predict the experimental cutting temperatures generated in orthogonal turning of AISI 316L stainless steel. Experimental and numerical analyses of the cutting forces were carried out to numerically obtain the cutting temperature. For this purpose, cutting tests were conducted using coated (TiCN + Al2O3 + TiN and Al2O3) and uncoated cemented carbide inserts. The Deform-2D programme was used for numerical modelling and the Johnson–Cook (J–C) material model was used. The numerical cutting forces for the coated and uncoated tools were compared with the experimental results. On the other hand, the cutting temperature value for each cutting tool was numerically obtained. The artificial neural network model was used to predict numerical cutting temperatures by means of the numerical cutting forces. The best results in predicting the cutting temperature were obtained using the network architecture with a hidden layer which has seven neurons and LM learning algorithm. Finally, the experimental cutting temperatures were predicted by entering the experimental cutting forces into a formula obtained from the artificial neural networks. Statistical results (R2, RMSE, MEP) were quite satisfactory. This demonstrates that the established ANN model is a powerful one for predicting the experimental cutting temperatures.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.