Prediction of the Cutting Depth of Abrasive Suspension Jet Using a BP Artificial Neural Network

Abstract

Abrasive suspension jet is a new embranchment of abrasive jet. In the cutting process of this jet, the suspension concentration is constant, so the cutting quality is more stable. In this paper, a prediction model based on a back-propagation (BP) artificial neural network is presented for predicting the cutting depth generated by abrasive suspension jet. In the application of the BP neural network, the mean error of the output in the model training is 0.01, the relatively discrepancy is below 8.70%. The modeling method based on the BP neural network is much more convenient and exact compared with traditional methods, and can always achieve a much better prediction effect. It is verified with experiments to be reasonable and feasible, and it is the better foundation for the future study of abrasive suspension jet.