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首页> 外文期刊>Structural Safety >Lifetime-oriented multi-objective optimization of structural maintenance considering system reliability, redundancy and life-cycle cost using GA
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Lifetime-oriented multi-objective optimization of structural maintenance considering system reliability, redundancy and life-cycle cost using GA

机译：考虑遗传算法的系统可靠性，冗余性和生命周期成本的结构维护的面向生命的多目标优化

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摘要

The need to design and construct structural systems with adequate levels of reliability and redundancy is widely acknowledged. It is as crucial that these desired levels are maintained above target levels throughout the life of the structure. Optimization has served well in providing safer and more economical maintenance strategies. Lifetime maintenance optimization based on system reliability has already been proposed. It is still needed, however, to incorporate redundancy in the lifetime maintenance optimization process. Treating both system reliability and redundancy as criteria in the lifetime optimization process can be highly rewarding. The complexity of the process, however, requires the automation of solving the optimization problem. Genetic algorithms (GAs) are used in this study to obtain solutions to the multi-objective optimization problems considering system reliability, redundancy and life-cycle cost (LCC). An approach to provide the optimization program the ability to optimally select what maintenance actions are applied, when they are applied, and to which structural components they are applied is presented. Two different strategies are proposed. The first strategy has the ability to optimally select mixed maintenance types to apply to different parts of the structure at the same time. This strategy can be used in cases where any combination of different maintenance options can be practically applied to any part of the structure. The application of this strategy on truss structures is shown in a numerical example. The second strategy can be used when a limited number of possibilities of practical maintenance options are available. The application of this strategy to bridge structures is shown in a numerical example. The greatest advantage of the proposed approach (both strategies) is its ability to avoid the application of maintenance interventions to structural components that are not critical.
机译：设计和构建具有足够可靠性和冗余度的结构系统的需求已得到广泛认可。同样重要的是，在整个结构寿命期间，将这些所需的水平保持在目标水平以上。优化在提供更安全，更经济的维护策略方面起到了很好的作用。已经提出了基于系统可靠性的终身维护优化。但是，仍然需要将冗余纳入寿命维护优化过程中。将系统可靠性和冗余性作为生命周期优化过程中的标准可能会非常有益。但是，过程的复杂性要求自动化解决优化问题。在本研究中，使用遗传算法（GA）获得考虑系统可靠性，冗余性和生命周期成本（LCC）的多目标优化问题的解决方案。提出了一种方法，使优化程序能够最佳地选择要应用哪些维护措施，何时应用维护措施以及将其应用于哪些结构部件。提出了两种不同的策略。第一种策略具有最佳选择混合维护类型以同时应用于结构的不同部分的能力。在不同维护选项的任意组合可以实际应用于结构的任何部分的情况下，可以使用此策略。数值示例显示了该策略在桁架结构上的应用。当可用的实际维护选项数量有限时，可以使用第二种策略。数值示例显示了该策略在桥梁结构中的应用。所提出的方法（两种策略）的最大优点是能够避免对非关键的结构部件应用维护措施。

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  • 来源
    《Structural Safety》 |2009年第6期|460-474|共15页
  • 作者

    Nader M. Okasha; Dan M. Frangopol;

  • 作者单位

    Department of Civil and Environmental Engineering, Center for Advanced Technology for Large Structural Systems (ATLSS), Lehigh University, Bethlehem, PA 18015-4729, USA;

    Department of Civil and Environmental Engineering, Center for Advanced Technology for Large Structural Systems (ATLSS), Lehigh University, Bethlehem, PA 18015-4729, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    structural systems; redundancy; reliability; maintenance; optimization; genetic algorithms;

    机译：结构系统;冗余;可靠性;保养;优化;遗传算法;

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