Effect of technological parameters on vibration acceleration in milling and vibration prediction with artificial neural networks<bold> </bold>

被引：2
|
作者：
Zagorski, Ireneusz [1 ]
Kulisz, Monika [2 ]
机构：
[1] Lublin Univ Technol, Dept Prod Engn, Fac Mech Engn, Nadbystrzycka 36, PL-20618 Lublin, Poland
[2] Lublin Univ Technol, Dept Org Enterprises, Fac Management, Nadbystrzycka 38, PL-20618 Lublin, Poland
来源：
III INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN ENGINEERING SCIENCE (CMES 18) | 2019年 / 252卷
关键词：
CHATTER SUPPRESSION; STABILITY;
D O I：
10.1051/matecconf/201925203015
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper reports on the study of vibration acceleration in milling and vibration prediction by means of artificial neural networks. The milling process, carried out on AZ91D magnesium alloy with a PCD milling cutter, was monitored to observe the extent to which the change of selected technological parameters (v(c), f(z), a(p)) affects vibration acceleration a(x), a(y) and a(z). The experimental data have shown a significant impact of technological parameters on maximum and RMS vibration acceleration. The simulation works employed the artificial neural networks modelled with Statistica Neural Network software. Two types of neural networks were employed: MLP (Multi-Layered Perceptron) and RBF (Radial Basis Function).<bold> </bold>
引用
收藏
页数：6
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