‌Optimization Design of Heavy-Duty Gears Based on an Improved Multi-Objective Genetic Algorithm

DOI: https://doi.org/10.62517/jbdc.202601306

Author(s)

Chen Su, Xiaolan Guo*, Yuxing Yuan, Rong Lan

Affiliation(s)

Institute of Intelligent Manufacturing, Panzhihua University, Panzhihua, Sichuan, Sichuan Province, China *Corresponding Author

Abstract

This paper carries out structural optimization for the gear transmission system applied on heavy mining vehicles, with an enhanced NSGA-II multi-objective genetic algorithm adopted as the core optimization tool. Three design objectives are set to build the multi-objective calculation model: cutting down the overall volume of gear pairs, raising the gear contact ratio and boosting the anti-fatigue performance of gear teeth. Meanwhile, key limiting conditions are taken into account during modeling, such as allowable contact fatigue stress, reasonable tooth quantity range and effective tooth face width.After the algorithm outputs the balanced optimal design scheme, transient dynamic simulation is conducted to check the actual working performance of the improved gear structure. The simulation data shows that the optimized gear assembly cuts total structural deformation by [X]%, delivers more uniform stress distribution on tooth surfaces and relieves the severe stress concentration existing in the initial structural scheme.From the above analysis results, the modified NSGA-II algorithm proves effective in multi-objective gear optimization, which greatly upgrades the comprehensive mechanical properties of heavy-load gear systems. The optimization framework proposed in this research can offer practical design references for similar mechanical transmission design projects.

Keywords

NSGA-Ⅱ; Heavy-Duty Gears; Optimization Design; Transient Analysis

References

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