Research On Adaptive Control Of Drilling Process With Oxide Casting

In the process of removal by drilling casting with the oxide coating,the surface hardness of the workpiece is large and the bit angle becomes larger,resulting in drill wear to speed up and shortening the life of the drill bit.In order to extend the life of the drill bit in this case,the following research work is carried out in this paper.(1)The relationship between the wear of the drill bit and the cutting parameters in drilling casting with oxide coating is studied.The hardness characteristics and bit characteristics of the casting with oxide layer are studied,and the reason of the tool wear is analyzed.The drilling force in the process of drilling the casting with oxide coating was analyzed by DEFORM-3D software.The results show that the influence of the feed rate on the axial force is significant,and the spindle speed has a great influence on the cutting torque.(2)The relationship between the motor current and the cutting torque,the axial force,and the relationship between the cutting torque,the axial force and the cutting parameters were investigated.The relationship between the spindle motor current and the cutting torque,the feed motor current and the axial force is obtained by experimentally obtaining the spindle motor current and the feed motor current during the drilling process under different cutting parameters.The relationship between the axial force and the cutting torque and the cutting parameters is obtained by the multiple regression analysis,and the indirect relationship between the motor current and the cutting parameters is obtained.In order to establish the relationship between the motor current and the cutting parameters,the neural network model is constructed to predict the cutting parameters.(3)Design and experimental verification of self-adaptive control system for drilling casting with oxide layer is carried out.Self-adaptive drilling control system,which is to extend bit life,is designed for the drilling oxide casting,including hardware design and software design.The system uses DSP to process the cutting parameters signal of the neural network model feedback,and uses the output pulse signal to control the spindle motor and the feed motor.An experimental platform with an adaptive control system for oxide casting is built.The effectiveness of the control system is verified by comparing the changes of the motor current before and after the self-adaptive control.The comparison of durability of the drill bit shows that the system can effectively improve the drill bit life.