کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7180789 1467845 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Indirect model for roughness in rough honing processes based on artificial neural networks
ترجمه فارسی عنوان
مدل غیر مستقیم برای زبری در فرآیندهای خرد کردن بر اساس شبکه های عصبی مصنوعی
کلمات کلیدی
افتخار زبری سطح، شبکه های عصبی مصنوعی، مدل غیر مستقیم
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
چکیده انگلیسی
In the present paper an indirect model based on neural networks is presented for modelling the rough honing process. It allows obtaining values to be set for different process variables (linear speed, tangential speed, pressure of abrasive stones, grain size of abrasive and density of abrasive) as a function of required average roughness Ra. A multilayer perceptron (feedforward) with a backpropagation (BP) training system was used for defining neural networks. Several configurations were tested with different number of layers, number of neurons and type of transfer function. Best configuration for the network was searched by means of two different methods, trial and error and Taguchi design of experiments (DOE). Once best configuration was found, a network was defined by means of trial and error method for roughness parameters related to Abbott-Firestone curve, Rk, Rpk and Rvk.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Precision Engineering - Volume 43, January 2016, Pages 505-513
نویسندگان
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