Research on performance prediction and optimization of road header based on regression model

Abstract

The drilling rate is one of the key parameters to measure the working performance of the road header. Set the drilling speed as the target variable, the quadratic regression model is established by using the master control parameters, such as cutter head torque, jack thrust, cutter head speed, and screw speed as design variables, then the prediction function of the drilling speed is obtained. The error of the regression function is determined by the fitting coefficient of determination, the modified coefficient of determination and the root mean square error, then the effect of different sample data mining methods on the fitting accuracy is studied. An optimization mathematical model is constructed. The quadratic programming algorithm is applied to solve the extreme values under different sample numbers, therefore, the tunneling performance is effectively improved. The research method has high computational efficiency, and the theoretical results are reliable.