Rolling Element Bearing Design Based on Improved Dung Beetle Optimization Algorithm

• Published in: 2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) Vol. 6; pp. 1961 - 1965
• Main Authors: Haiyu, Luo, Haohao, Ma, Runze, Dai, Xuping, Wu, Asarry, Azizan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.05.2024
• Subjects: Bearing design; DBO algorithm; Heuristic algorithms; journal diameter; Optimization methods; Problem-solving; Reliability engineering; Rolling bearings; Rolling Element Bearing; Sociology; Technological innovation
• ISSN: 2693-2776
• DOI: 10.1109/IMCEC59810.2024.10575193

Rolling element bearings are an important component in many mechanical systems, and optimizing their design is critical to improving performance and reliability. This paper uses an improved dung beetle optimization (DBO) algorithm to design rolling bearings. The DBO algorithm is inspired by the foraging behavior of dung beetles and is used to solve many practical engineering problems. This study aims to improve the dynamic load-carrying capacity of rolling element bearings and optimize design parameters such as journal diameter, ball diameter, inner and outer raceway curvature coefficient, total number of rolling elements, contact angle, and geometry. The dynamic load capacity of the designed bearing (D=160, d=90, Bw=30) reaches 85.549kN. Experiments prove that the improved DBO algorithm can obtain optimal design parameters more efficiently than the original DBO algorithm. Applying swarm intelligence algorithms to practical engineering problem-solving to obtain feasible solutions that meet performance goals will contribute to the advancement of mechanical engineering and optimization methods.