Research on Thermal Deformation of Electric Axis Based on Improved Salpa Swarm Algorithm

The primary factor influencing the precision of CNC machine tools during machining is the thermal distortion of the motorized spindle. Due to the pronounced nonlinear characteristics of the critical parameter, the coefficient of thermal expansion significantly influences the thermal deformation of the motorized spindle, finding a precise coefficient remains challenging. This complexity poses difficulties in enhancing the machining accuracy of the motorized spindle effectively. The optimization of the thermal deformation model for the spindle involves refining the coefficient of thermal expansion through the enhanced Salp swarm algorithm. Furthermore, a thermal deformation model for the spindle is introduced, leveraging the advanced Salp swarm algorithm. Using the 100MD60Y4 electric spindle as the controlled experimental object, thermal deformation research was conducted on the electric spindle at varying velocities. The findings indicate that employing the enhanced optimization algorithm for the Thalassia thaliacea group yields a coefficient of thermal expansion that reduces the predicted thermal deformation error. This outcome brings the predicted values closer to the actual measured values, enhancing overall accuracy compared to results obtained with empirical coefficients of thermal expansion.