DocumentCode :
1945866
Title :
Study on machining prediction in plane grinding based on artificial neural network
Author :
Yang, Qingqing ; Jin, Jue
Author_Institution :
Software Coll., Ningbo Dahongying Univ., Ningbo, China
fYear :
2010
fDate :
15-16 Nov. 2010
Firstpage :
442
Lastpage :
444
Abstract :
A new approach based on an artificial neural network (ANN) is presented for the forecasting of machining precision of plane grinding. The ANN model is based on GCAOBP (Globally Convergent Adaptive Quick Back Propagation) algorithm. A genetic algorithm (GA) was then applied to the trained ANN model to predict the machining precision. The integrated GCAOBP-GA algorithm was successful in predicting the value of PV (Peak to Valley) of machined workpiece using the machining environment parameters. The results of verification experiments have shown that the PV of workpiece profile in plane grinding process can be predicted effectively through this approach.
Keywords :
genetic algorithms; grinding; machining; neural nets; production engineering computing; ANN model; GCAOBP algorithm; artificial neural network; genetic algorithm; globally convergent adaptive quick back propagation algorithm; integrated GCAOBP-GA algorithm; machining prediction; peak to valley; plane grinding process; Adaptation model; Artificial neural networks; Biological cells; Machining; Prediction algorithms; Training; Wheels; artificial neural network; genetic algorithm; plane grinding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems and Knowledge Engineering (ISKE), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-6791-4
Type :
conf
DOI :
10.1109/ISKE.2010.5680832
Filename :
5680832
Link To Document :
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