It is difficult to establish a cutting model using traditional mathematical methods for the abrasive water jet because of the complex nonlinear relationship between the cutting performance and the influencing factors.A BP neural network cutting model of abrasive water jet,which contains six influencing factors as jet pressure,abrasive flow,cutting target distance,work piece thickness,abrasive nozzle diameter and cutting speed,was established based on BP artificial neural network theory and the results of the cutting experiment with typical material.A portable abrasive water jet cutting speed artificial neural network prediction unit was developed to realize the visualization of the network model based on Delphi,providing conditions for the integration of network model and NC system.The results showed that the network model integrated with NC system can predict the cutting speed rapidly,and accurately reliably and realize the effective control of the cutting quality.
