Fundamental Researh On Cutting Model Of Abrasive Water Jet For Aluminum Alloy

There is no environmental pollution and thermal damage in the cutting process of abrasive water jet.Among the current processing methods,abrasive water jet processing,as a newly emerged processing way,is a cold processing method.Due to its unique characteristics,it can be said to be a revolution in the processing field and has broad application in many industries.In this paper,through the particle erosion theory,analyzing the material cutting process on a single abrasive particle microscopically;Analyzing five parameters which is the abrasive water jet's traverse speed,jet pressure,abrasive particle size,abrasive flow rate and target distance.Analyzing their impact on cutting quality.The aluminum alloy(AL7075-T6)was used as the test piece for the abrasive water jet cutting experiment.Through a single factor experiment,determining the reasonable process parameters.Orthogonal experiment was carried out,and through the analysis of range,the best combination of process parameters and the importance of five process parameters on cutting quality was obtained.A regression model of abrasive water jet cutting for aluminum alloy was established,and it was verified.The relative error of the predicted value is within the allowable range.According to the cutting experiment data,establishing a model for aluminum alloy of abrasive water jet cutting based on BP neural network,and the model was simulated and verified to detect the performance of the neural network model,comparing the 6 sets data of testing.The absolute value of the maximum relative error between the predicted roughness of the cutting section and the roughness of the actual cutting section is 9.09%,which indicates that the model of abrasive water jet cutting for aluminum alloy based on BP neural network has high accuracy.In order to further improve the accuracy of the model of the abrasive water jet cutting for aluminum alloy,the RBF neural network was used to establish a model of the cutting process of the abrasive water jet for aluminum alloy,and the improvement of the model accuracy was verified by this method.On the other hand,the GRNN neural network was used to establish an aluminum alloy cutting model,and the accuracy of the model based on the GRNN neural network was verified,the relative prediction error was smaller.By comparing the output results of two cutting models,for the purpose of improving the accuracy of the model,the model based on GRNN neural network has higher accuracy and smaller prediction error.