Research on prediction model of drilling force in CFRP internal chip removal hole drilling based on SVR

Abstract Drilling force is the main factor affecting the drilling quality and tool wear of carbon fiber reinforced resin matrix composites (CFRP), selecting the appropriate process parameters can effectively control the drilling force, improve the drilling quality and tool life. In this paper, in order to accurately predict and effectively control the drilling force under the process of internal chip removal hole drilling: Firstly, based on the application of support vector regression (SVR) in data analysis, the theory of the prediction model of drilling force in CFRP is given; Secondly, on the basis of the above theories, the experiment of chip removal in CFRP is designed and completed, designed and completed the CFRP internal chip removal processing drilling experiment, it provides preparation for the solution of parameters in the subsequent model; Again, based on the above theoretical analysis and experimental data, under the premise of choosing the appropriate kernel function and loss function, the sequential minimum optimization (SMO) algorithm is applied to solve the unknown parameters in the model, to complete the construction of the SVR-based CFRP internal chip removal machining drilling force prediction model; Finally, using the constructed predictive model, it is predicted that when CFRP internal chip removal hole machining is studied, The relationship between cutting parameters (speed, feed), tool parameters (drill diameter, peak angle, relief angle) and suction parameters (negative pressure) and axial force.