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Gear pair design optimization by Genetic Algorithm and FEA

机译:基于遗传算法和有限元分析的齿轮副设计优化

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Multiple, often conflicting objectives arise naturally in most real-world optimization. Gear is a mechanical device that transfers the rotating motion and power from one part of a machine to another. Searching for best gear is a very hard problem. Gear optimization can be divided into two categories, namely, single gear pair or Gear train optimization. The problem of gear pairs design optimization is difficult to solve because it involves multiple objectives and large number of variables. Therefore a reliable and robust optimization technique will be helpful in obtaining optimal solution for the problems. In this paper an attempt has been made to optimize spur gear pair design using Genetic Algorithm (GA) and analytical tool MITCalc. A combined objective function which maximizes the Power, Efficiency and minimizes the overall Weight, Centre distance has been considered in this model. Finite Element Analysis (FEA) was carried out and results were compared with the allowable limit.
机译:在大多数现实世界中的优化中,自然会出现多个通常相互冲突的目标。齿轮是一种机械装置,可将旋转运动和动力从机器的一部分传递到另一部分。寻找最佳装备是一个非常困难的问题。齿轮优化可分为两类,即单齿轮对或齿轮系优化。齿轮副设计优化的问题很难解决,因为它涉及多个目标和大量变量。因此,可靠而强大的优化技术将有助于获得问题的最佳解决方案。本文尝试使用遗传算法(GA)和分析工具MITCalc优化正齿轮对的设计。在此模型中考虑了一个组合目标函数,该函数最大化了功率,效率并最小化了总重量,中心距。进行了有限元分析(FEA),并将结果与​​允许极限进行了比较。

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