Optimization Design of Thin Wall Angular Contact Ball Bearing Based on MATLAB Genetic Algorithm

Abstract

Abstract The bearing for industrial robots is desired to have a long service life. To address that, an optimization study was conducted on a thin wall angular contact ball bearing used for a robot. Firstly, an optimization model was established with the basic rated life as the objective function and the curvature radius coefficient of the inner ring groove, curvature radius coefficient of the outer ring groove, ball diameter, pitch diameter, and the number of balls as the design variables. Then, taking the angular contact ball bearing ZR76/82C as an example, the optimization model was solved quickly based on a genetic algorithm via MATLAB software in two ways: calling the ga function and optimization toolbox, and the optimal structural parameters of the bearing were obtained. After the optimization, the basic rated life of the bearing was increased by 52%. The orthogonal test optimization design method was applied to validate the calculations, and the validation results showed that the two optimization results were very close to each other. The results show that the two approaches based on MATLAB genetic algorithm are efficient and feasible for solving optimization issues, and are of reference value for the study of solving other optimization issues.