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Anti-Defect Design for Mechanical Elements under Severe Condition Based on a Half-Real Defect Model

机译:基于半真实缺陷模型的严重状况下的机械元件反缺陷设计

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For mechanical elements running under severe working condition, there inevitably exist some small defects caused during working. The weak area, which is sensitive to defects, of the structure is more vulnerable, resulting in early damage during service. This paper describes a novel anti-defect design method for optimizing structure to enhance the reliability of vulnerable areas. First, a half-real defect model derived from the real defect is developed to model the geometrical characteristics of defects. Then, the damage degrees of model parameters are identified by Sobol’s sensitivity method and the vulnerable area can be labeled according to the damage degree. Finally, we take the vulnerable area as the object of anti-defect optimization for structure and the optimization variables are selected tendentiously based on parameters with larger damage degrees. The multiobjective particle swarm algorithm is then employed to find the optimal distribution of the variables in order to improve the safety of the sensitive area of structure. We take the impeller blade as the research subject to verify the validity of the proposed method. Analysis results showed that the proposed method can increase the structure strength and delay the damage of the mechanical elements.
机译:对于在严重的工作条件下运行的机械元件,在工作期间不可避免地存在一些小缺陷。结构对缺陷敏感的弱区域更脆弱,导致服务期间的早期损坏。本文介绍了一种新型的防缺陷设计方法,用于优化结构,以提高弱势区域的可靠性。首先,开发了从实际缺陷导出的半实际缺陷模型,以模拟缺陷的几何特征。然后,通过Sobol的灵敏度方法识别模型参数的损伤程度,并且可以根据损坏程度标记易受攻击的区域。最后,我们将脆弱的区域作为结构的防缺陷优化对象,并且基于具有较大损伤度的参数选择优化变量。然后采用多目标粒子群算法来查找变量的最佳分布,以提高结构敏感区域的安全性。我们将叶轮刀片作为研究,以验证所提出的方法的有效性。分析结果表明,该方法可以提高结构强度并延缓机械元件的损坏。

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