Abstract: For thermal model of machine tool spindle system, a multi-parameter and multi-objective correction method is presented, which is hybrid response surface model and multi-objective genetic algorithm (MOGA). Based on the thermal characteristic ( temperature and thermal deformation ) datum of spindle system from thermal equilibrium test, the central composite experiment design method and surface response method are combined to establish the second-order surface models of thermal characteristic for the multi-parameter finite element thermal model of spindle system. Then these surface models are optimized by employing the approximation loop technique of MOGA, and a distributed Pareto solution set is obtained. Finally, the accuracy of initial thermal model is improved. Taking a double spindle system of one precision CNC grinder as an example, the thermal model which included four input parameters and two output parameters is corrected with temperature and thermal deformation from thermal equilibrium test. It is shown that the model correction method can use the test datum effectively, and obtain the optimal solution for corrected parameters by limited simulation. The method is suitable for multi-parameter and multi-objective correction of complex model, which can reduce the model calculation error and make the correction model analysis results more realistic.

Key words: thermal model correction;thermal equilibrium test;spindle system;response surface model;multi-objective genetic algorithm