A thermal error prediction model of the motorized spindles based on ABHHO-LSSVM

Thermal error compensation of high-speed motorized spindle is one of the effective methods to improve the machining accuracy of CNC machine tools. In this paper, the variation law of the thermal error of the motorized spindle is studied, a method for selecting temperature sensitive points is proposed, and the thermal error prediction model is established. First, the temperature and thermal error of the motorized spindle at different speeds are measured by thermal error experiment. Secondly, the clustering by fast search and find of density peaks (CFSFDP) is used to solve the problem that the optimal cluster number is unknown in the process of selecting temperature sensitive points, and the temperature sensitive points under multi speed of the motorized spindle are obtained. Finally, the adaptive boundary harris hawk algorithm (ABHHO) is used to optimize the hyperparameters of the least squares support vector machine (LSSVM), and a prediction model for the thermal error based on ABHHO-LSSVM is established, which improves the prediction accuracy. The proposed method and model provide a technical basis for thermal error compensation of motorized spindle.