Research On Cutting Taper Characteristics Of Abrasive Water Jet

As one of the fastest growing special processing technologies in the world,abrasive water jet machining technology is widely used in various industrial production because of its unique cold processing mode,especially for the processing of heat sensitive,pressure sensitive and other difficult-to-machine materials.The research on cutting taper characteristics of abrasive water jet is beneficial to the development of intelligent and high-precision water jet special machining technology.In this thesis,the taper mechanism of abrasive water jet is analyzed theoretically from both micro and macro aspects,and the cutting profile is defined.The aluminum alloy(AI6061-T6)plate was used for abrasive water jet cutting test.By analyzing the specific weight among the four process parameters,namely jet pressure,abrasive flow rate,material thickness and cutting speed,were selected for single factor test.The results show that material thickness and cutting speed have great influence on trimming taper,while jet pressure and abrasive flow rate have little influence on trimming taper.The regression model of cutting taper of abrasive water jet is established based on cutting experimental data,and its fitting accuracy is R^2=0.91019.Nine groups of test samples prove that the regression model has high reliability and fitting,at the same time,it provides a certain reference for the subsequent neural network model.Based on the experimental data,the trimming taper is modeled based on RBF neural network,and the training sample data is optimized by interp2 function.By comparing the experimental value with the predicted value,the mean square error between the predicted value and the experimental value is 8.81541e-04,and the absolute value of relative error is 8.124952 e-02°.Other predicted values are very close to the experimental values,so the prediction accuracy meets the requirements of abrasive water jet machining.By comparing the prediction results of the above two models,the cutting taper model based on RBF neural network has higher prediction accuracy,smaller overall prediction error and stronger real-time performance.Taking rectangular and cylinder shape parts as examples,the experimental research on abrasive water jet cutting and taper compensation is carried out.By introducing the actual process parameters into the cutting taper model,the trimming taper of the workpiece during cutting is predicted,and the taper compensation cutting experiment is carried out,and the better taper compensation effect is obtained.