Title :
A neural network-based model for the prediction of cutting force in milling process. A progress study on a real case
Author :
Alique, Angel ; Haber, Rodolfo E. ; Haber, Rodolfo H. ; Ros, Salvador ; Gonzalez, Carlos
Author_Institution :
Inst. de Automatica Ind., CSIC, Madrid, Spain
Abstract :
In spite of recent developments focusing on milling process optimization through an effective cutting force control, there is a need for the analysis of the transient response of these systems because undesirable oscillations in cutting force can be harmful to the quality of the finishing surface and tools. The main goal of this work is to develop a versatile neural network model which can online predict the mean cutting force under commonly encountered conditions. Using this model, easily obtained from a straightforward machining test, developments of complex adaptive controllers and monitoring systems can be carried out. As a result, a good model for predicting the cutting process was obtained
Keywords :
adaptive control; condition monitoring; cutting; force control; machining; multilayer perceptrons; neurocontrollers; optimisation; predictive control; transient response; adaptive control; cutting force; force control; machining; milling; monitoring; multilayer perceptron; neural network; process optimization; transient response; Force control; Machining; Milling; Neural networks; Predictive models; Programmable control; Surface finishing; System testing; Transient analysis; Transient response;
Conference_Titel :
Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on
Conference_Location :
Rio Patras
Print_ISBN :
0-7803-6491-0
DOI :
10.1109/ISIC.2000.882910