Optimal volume design of planetary gear train using particle swarm optimization

Kaoutar Daoudi, El Mostapha Boudi
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引用次数: 4

Abstract

Planetary gear train are widely used for power transmission in industrial mechanic. The problem of minimum volume of simple and multi-stage planetary gear systems has been a subject of considerable interest. This paper presents a comparison between two advanced optimization algorithms known as Genetic algorithm (GA) and particle swarm optimization (PSO) to find the optimal combination of design parameters for minimum volume of planetary gear train. This study, describe the algorithm and the mathematical model the PSO technique. However, for the GA we are based on the previously published results.
基于粒子群算法的行星轮系体积优化设计
行星轮系在工业机械中广泛应用于动力传动。简单和多级行星齿轮系统的最小体积问题一直是一个相当感兴趣的主题。对遗传算法(GA)和粒子群算法(PSO)两种先进的优化算法进行了比较,寻找行星轮系体积最小的设计参数的最优组合。本研究描述了粒子群算法及其数学模型。然而,对于遗传算法,我们是基于先前发表的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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