Optimal design of cross shaft based on multi-objective genetic algorithm. (13th February 2022)

• Record Type: Journal Article
• Authors: Mao, Yanfeng; Li, Gongfa; Jiang, Du; Tao, Bo; Cao, Yongcheng; Li, Shidong; Sun, Nannan; Li, Zeshen
• Is Part Of: International journal of wireless and mobile computing. Volume 21:Number 3(2021)
• Page Start: 243
• Page End: 254
• Publication Date: 2022-02-13
• Subjects: cross shaft -- sensitivity analysis -- structure optimisation -- response surface optimisation -- multi-objective genetic algorithm; Mobile computing -- Periodicals; Wireless communication systems -- Periodicals; 004.6
• Languages: English
• ISSNs: 1741-1084

Abstract

The cross shaft is the crucial component for torque transmission in the coupling. In general, the cross shaft is prone to fatigue and deformation due to the ample torque and the unreasonable structure of the bearing. In this paper, the key dimensional parameters of the cross shaft are screened based on the sensitivity analysis. Next, these dimensions were taken as design variables, and the optimisation objectives were to reduce the maximum equivalent stress and the maximum total deformation. Finally, the multi-objective genetic algorithm is used to complete the optimisation design of the cross shaft. The maximum total deformation of the cross shaft is reduced by 0.4717 mm, and the maximum equivalent stress is reduced by 130.35 MPa compared with the initial structure.