DocumentCode
2615171
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
fYear
2000
fDate
2000
Firstpage
121
Lastpage
125
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on
Conference_Location
Rio Patras
ISSN
2158-9860
Print_ISBN
0-7803-6491-0
Type
conf
DOI
10.1109/ISIC.2000.882910
Filename
882910
Link To Document