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Reliability-based design optimization for flexible mechanism with particle swarm optimization and advanced extremum response surface method

机译:基于粒子群优化和高级极值响应面法的柔性机构基于可靠性的设计优化

摘要

To improve the computational efficiency of the reliability-based design optimization (RBDO) of flexible mechanism, particle swarm optimization-advanced extremum response surface method (PSO-AERSM) was proposed by integrating particle swarm optimization (PSO) algorithm and advanced extremum response surface method (AERSM). Firstly, the AERSM was developed and its mathematical model was established based on artificial neural network, and the PSO algorithm was investigated. And then the RBDO model of flexible mechanism was presented based on AERSM and PSO. Finally, regarding cross-sectional area as design variable, the reliability optimization of flexible mechanism was implemented subject to reliability degree and uncertainties based on the proposed approach. The optimization results show that the cross-section sizes obviously reduce by 22.96 mm2 while keeping reliability degree. Through the comparison of methods, it is demonstrated that the AERSM holds high computational efficiency while keeping computational precision for the RBDO of flexible mechanism, and PSO algorithm minimizes the response of the objective function. The efforts of this work provide a useful sight for the reliability optimization of flexible mechanism, and enrich and develop the reliability theory as well.
机译:为了提高柔性机构基于可靠性的设计优化(RBDO)的计算效率,提出了将粒子群优化(PSO)算法和高级极值响应面方法相结合的粒子群优化-极端极值响应表面方法(PSO-AERSM)。 (AERSM)。首先开发了AERSM,并基于人工神经网络建立了数学模型,并研究了PSO算法。然后提出了基于AERSM和PSO的RBDO柔性机构模型。最后,以截面积为设计变量,在此基础上,基于可靠性和不确定性,对柔性机构进行了可靠性优化。优化结果表明,在保持可靠性的同时,截面尺寸明显减小了22.96 mm2。通过方法比较,证明了AERSM在保持柔性机构的RBDO计算精度的同时,保持了较高的计算效率,而PSO算法则使目标函数的响应最小化。这项工作为柔性机构的可靠性优化提供了有益的参考,也丰富和发展了可靠性理论。

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