High-speed electric spindle is an important part of CNC machining equipment. The thermal displacement generated by the electric spindle during operation is the main reason that affects the machining stability and machining accuracy of the electric spindle. Compensating the thermal error of the high-speed electric spindle can effectively improve the CNC machining. The processing performance of the equipment. Therefore, it is particularly important to establish the accuracy of the thermal error prediction model. Taking the A02 high-speed electric spindle as the research object, ANSYS is used to analyze the thermal characteristics of the electric spindle, and the temperature and thermal displacement monitoring points of the electric spindle are arranged according to the simulation results, and the temperature and thermal displacement data of the monitoring points under different rotational speeds are collected; Using K-means to classify temperature measurement points, uses the grey relation analysis degree to determine the correlation between the temperature measurement point and the thermal displacement data, and selects 4 temperature sensitive points from 10 temperature measurement points. Finally, particle swarm optimization (PSO) is used to optimize the penalty factor and kernel function of support vector machine (SVM), and the PSO-SVM prediction model is established to compare with the neural network prediction model of SVM and genetic algorithm (GA) optimized SVM respectively. The results show that PSO-SVM has better robustness, stability and generalization ability.

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High-speed motorized spindle is an important component of machine tool, and the influence of heat and deformation generated in the working process on the machining accuracy cannot be ignored. In order to reduce the temperature of the motorized spindle in the machining process, this paper first explore the influence of the flow rate of the motorized spindle cooling water on the cooling water jacket and the overall temperature change. The results indicate that when the flow rate exceeds a certain range, the overall temperature no longer drops, so there is an optimal flow rate in the choice of flow rate. Secondly, to solve the problem of uneven axial temperature distribution of the traditional spiral water jacket, four kinds of cooling water jackets with different structures were proposed. The simulation results show that the difference of temperature distribution inside the serpentine water jacket is small, the overall temperature was reduced by 1.8℃ and the pressure drop was reduced by 62.54kPa. It shows that the serpentine cooling water jacket has better cooling performance and can effectively reduce the thermal deformation of the motorized spindle shafting, so as to achieve the purpose of improving the machining accuracy.