Modelling of abrasive flow machining process: a neural network approach

摘要

A simple neural network model for abrasive flow machining process has been established. The effects of machining parameters on material removal rate and surface finish have been experimentally analysed. Based on this analysis, model inputs andoutputs were chosen and off-line model training using back-propagation algorithm was carried out. Simulation results confirm the feasibility of this approach and show a good agreement with experimental and theoretical results for a wide range of machining conditions. Learning could remarkably be enhanced by training the network with noise injected inputs.