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Comparative study on optimum design of rolling element bearing

机译:滚动轴承优化设计的比较研究

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Long fatigue life is the most important objective in the optimum design of rolling element bearing. In the present study the fatigue life of a radial ball bearing is maximized. The nonlinear constrained optimization problem has been solved using particle swarm optimization algorithm and a hybrid PSO and Teaching Learning based Optimization algorithm. The algorithm uses a ranking method of constraint handling and contact stress has been introduced as a new constraint. The results have been compared with the established available results. A constraint violation study has been carried out to prioritize the constraints. A convergence study has been performed to identify the key design variables. Encouraging results in terms of objective function values and CPU time have been reported in this study. (C) 2015 Elsevier Ltd. All rights reserved.
机译:疲劳寿命长是滚动轴承优化设计的最重要目标。在本研究中,径向球轴承的疲劳寿命达到了最大。非线性约束优化问题已使用粒子群优化算法和混合PSO和基于教学学习的优化算法解决。该算法使用约束处理的排序方法,并且已将接触应力作为新约束引入。将结果与已建立的可用结果进行了比较。进行了一项违反约束的研究,以优先考虑约束。已经进行了收敛研究以识别关键设计变量。在这项研究中,报告了关于目标函数值和CPU时间的令人鼓舞的结果。 (C)2015 Elsevier Ltd.保留所有权利。

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