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Optimization Design of the Geared Rotor System with Critical Speed Constraints Using the Enhanced Genetic Algorithm

机译:基于改进遗传算法的临界转速齿轮转子系统优化设计。

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This paper presents an efficient enhanced genetic algorithm to minimize the shaft weight, the unbalance response and the response due to the transmission error simultaneously. The minimization plays an important role in designing the geared rotor system under critical speed constraints. In the process of optimization, the design variables consist of shaft inner radii, bearing stiffness and the gear mesh stiffness. The enhanced genetic algorithm of optimization comprises the Hybrid Genetic Algorithm (HGA) and the Interval Genetic Algorithm (IGA). The HGA deals with this optimal design problem and the IGA accomplishes the interval optimization design. The results show that the presented enhanced genetic algorithm can not only effectively reduce the shaft weight and the transmission error response, but also precisely determine the interval ranges of design variables with feasible corresponding objective error.
机译:本文提出了一种有效的增强遗传算法,可将轴重,不平衡响应和传输误差引起的响应同时最小化。在临界转速约束下,最小化在设计齿轮转子系统中起着重要作用。在优化过程中,设计变量包括轴内半径,轴承刚度和齿轮啮合刚度。改进的优化遗传算法包括混合遗传算法(HGA)和区间遗传算法(IGA)。 HGA处理此最佳设计问题,而IGA完成间隔优化设计。结果表明,所提出的改进遗传算法不仅可以有效地减轻轴重和传递误差的响应,而且可以精确地确定设计变量的区间范围,并具有相应的客观误差。

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