Robust Optimization Method of Cylindrical Roller Bearing by Maximizing Dynamic Capacity Using Evolutionary Algorithms  

作　　者：Kumar Gaurav Rajiv Tiwari Twinkle Mandawat 

机构地区：[1]Department of Mechanical Engineering,Indian Institute of Technology Guwahati,Guwahati 781039,India

出　　处：《Journal of Harbin Institute of Technology(New Series)》2022年第5期20-40,共21页哈尔滨工业大学学报（英文版）

摘　　要：Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,have a minimum possible value and do not exceed the upper limit of a desired range of percentage variation.Also,it checks the feasibility of design outcome in presence of manufacturing tolerances in design variables.For any rolling element bearing,a long life indicates a satisfactory performance.In the present study,the dynamic load carrying capacity C,which relates to fatigue life,has been optimized using the robust design.In roller bearings,boundary dimensions(i.e.,bearing outer diameter,bore diameter and width)are standard.Hence,the performance is mainly affected by the internal dimensions and not the bearing boundary dimensions mentioned formerly.In spite of this,besides internal dimensions and their tolerances,the tolerances in boundary dimensions have also been taken into consideration for the robust optimization.The problem has been solved with the elitist non-dominating sorting genetic algorithm(NSGA-II).Finally,for the visualization and to ensure manufacturability of CRB using obtained values,radial dimensions drawing of one of the optimized CRB has been made.To check the robustness of obtained design after optimization,a sensitivity analysis has also been carried out to find out how much the variation in the objective function will be in case of variation in optimized value of design variables.Optimized bearings have been found to have improved life as compared with standard ones.

关 键 词：cylindrical roller bearing OPTIMIZATION robust design elitist non-dominating sorting genetic algorithm(NSGA-II) fatigue life dynamic load carrying capacity 

分 类 号：TH122[机械工程—机械设计及理论]