Optimization of structure parameters for angular contact ball bearings based on Kriging model and particle swarm optimization algorithm

To achieve the heat generation of an angular contact ball bearing, especially when confronted with a difficult challenge, is a complexity of numerical and analytical models of bearings. A combination method of the Kriging model and particle swarm optimization algorithm is proposed for optimizing structure parameters of the bearing to obtain the minimum heat generation of the bearing. Therefore, the heat generation and stiffness of the angular contact ball bearing, which are acquired based on pseudo statics analysis and raceway control theory of the bearing, are the optimization goal and constraint condition, respectively, that are used in particle swarm optimization. Taking the angular contact ball bearing NSK-7016A5 as an example, the results show that the total heat generation of the bearing is decreased and that the axial stiffness of the bearing is increased by optimizing the structure parameters of the bearing. In the end, the combination method that uses both Kriging and particle swarm optimization to optimize the structure parameters of the bearing could obtain satisfactory design results and increased bearing design efficiency; it also bears the potential for the design parameter optimization of other mechanical structures, which may lead to better design results.