Artificial Neural Network Modelling of Vibration in the Milling of AZ91D Alloy

Advances in Sciences and Technology

Monika Kulisz¹  Ireneusz Zagórski²  Anna Malec³  Aleksandra Semeniuk³ 

[1] Department of Organisation of Enterprises, Faculty of Management, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland;Department of Production Engineering, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland;Student of Production Engineering, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland;

关键词: simulation;    artificial neural networks;    vibration;    high-speed dry milling;    magnesium alloys;    chatter in milling;   

DOI  :  10.12913/22998624/76546

来源: DOAJ

【 摘 要 】

The paper reports the results of artificial neural network modelling of vibration in. a milling process of magnesium alloy AZ91Dby a TiAlN-coated carbide tool. Vibrations in machining processes are regarded as an additional, absolute machinability index. The modelling was performed using the so-called “black box” model. The best fit was determined for the input and output data obtained from the machining process. The simulations were performed by the Statistica software using two types of neural networks: RBF (Radial Basis Function) and MLP (Multi-Layered Perceptron).

【 授权许可】

Unknown