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Study on Optimal Design of Planetary Gear Reducer Based on Particle Swarm Algorithm and Matlab

机译:基于粒子群算法和Matlab的行星齿轮减速器优化设计研究。

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Planetary gear reducer is a typical device of power or motion transmission. The design of power planetary gear reducer may lead to significant effects on manufacturing, maintenance, operation and usability of an entire mechanical system. The optimal design of planetary gear reducer is to improve its loading capacity when its volume is reduced, weight lighted, efficiency raised and its service life prolonged. The optimization design of planetary gear reducer is a Constrained Optimization problem (CO). Compared with deterministic methods and Genetic Algorithms (GA), Particle Swarm Optimization Algorithm (PSO) is a good method in solving planetary gear reducer optimal problem. In this paper, we mainly introduce the optimal design of planetary gear reducer based on Particle Swarm Optimization Algorithm and MATLAB. Directed by the theory of Particle Swarm Optimization Algorithm, the complex planetary gear reducer optimal design model with eight design variables and eighteen inequality constraints conditions is established. When the model is simulated in MATLAB the minimal optimal value of variables and weight of planetary gear reducer can be obtained. Simulating Result shows that Particle Swarm Optimization is practical in solving complicated optimal design problems and effectively on avoiding constraint of solution and the optimal design of planetary gear reducer can be realized.
机译:行星齿轮减速器是动力或运动传递的典型装置。动力行星齿轮减速器的设计可能会对整个机械系统的制造,维护,操作和可用性产生重大影响。行星齿轮减速器的最佳设计是在减小其体积,减轻重量,提高效率并延长其使用寿命时提高其负载能力。行星齿轮减速器的优化设计是一个约束优化问题(CO)。与确定性方法和遗传算法(GA)相比,粒子群优化算法(PSO)是解决行星齿轮减速器最优问题的一种很好的方法。本文主要介绍基于粒子群算法和MATLAB的行星齿轮减速器的优化设计。以粒子群算法的理论为指导,建立了具有八个设计变量和十八个不等式约束条件的复杂行星齿轮减速器最优设计模型。当在MATLAB中对模型进行仿真时,可以获得变量的最小最佳值和行星齿轮减速器的重量。仿真结果表明,粒子群算法可以解决复杂的最优设计问题,有效地避免了求解的约束,可以实现行星齿轮减速器的最优设计。

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