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Multi-stage approach for structural damage identification using modal strain energy and evolutionary optimization techniques

机译:基于模态应变能和进化优化技术的结构损伤识别多阶段方法

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摘要

Deterioration and degradation of aging structures is a major concern worldwide. It is often necessary to evaluate the integrity of such structural systems. Early detection and eventual quantification of damage are important for improved safety, to prevent potential catastrophic events, and to extend the service life by repairing/retrofitting the components of the structure. Different methodologies have been proposed in the literature for the identification and localization of damage based on optimization techniques and modal-based approaches. The main drawback in using the optimization approach based on evolutionary algorithms is that it requires the evaluation of the objective function for the total population in each generation. As this is computationally intensive, in this study, a multi-stage approach has been proposed. In this, at first, localization of the damage was achieved so as to reduce the number of parameters of the objective function in the optimization approach. These identified damaged elements were analyzed further for exact identification and quantification of the damage using genetic algorithm (GA)-based optimization approach. To demonstrate the efficiency of the proposed hybrid approach, numerical studies have been carried out on selected structures. The approach of using modal strain energy change ratio to identify damage at first-stage identification is found to be very useful in reducing the objective function parameters in the optimization method. This multi-stage approach is found to be very efficient in the exact identification and quantification of damage in structures. The proposed approach could be used for identifying damage in large-scale structures.
机译:老化结构的恶化和退化是全世界主要关注的问题。通常有必要评估此类结构系统的完整性。对损坏进行早期检测和最终量化对于提高安全性,防止潜在的灾难性事件以及通过维修/翻新结构部件来延长使用寿命非常重要。基于优化技术和基于模态的方法,文献中已经提出了不同的方法来识别和定位损坏。使用基于进化算法的优化方法的主要缺点是,它需要评估每一代总人口的目标函数。由于这是计算密集型的,因此在本研究中,提出了一种多阶段方法。在这种情况下,首先实现损伤的定位,以减少优化方法中目标函数的参数数量。使用基于遗传算法(GA)的优化方法,对这些已识别的损坏元素进行了进一步分析,以准确识别和量化损坏。为了证明所提出的混合方法的效率,已经对选定的结构进行了数值研究。发现在第一阶段识别中使用模态应变能变化率识别损伤的方法对于减少优化方法中的目标函数参数非常有用。发现这种多阶段方法在准确识别和量化结构中的损坏方面非常有效。所提出的方法可用于识别大型结构中的损坏。

著录项

  • 来源
    《Structural health monitoring》 |2011年第2期|p.219-230|共12页
  • 作者单位

    Structural Engineering Research Centre (Council of Scientific and Industrial Research), CSIR Campus,TTTI ((Post), Taramani, Chennai 600 113, Tamil Nadu, India;

    Structural Engineering Research Centre (Council of Scientific and Industrial Research), CSIR Campus,TTTI ((Post), Taramani, Chennai 600 113, Tamil Nadu, India;

    Department of Civil and Structural Engineering, Annamalai University,Annamalainagar 608 002, Tamil Nadu, India;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    damage detection; vibration data; modal strain energy; genetic algorithm; optimization;

    机译:损坏检测;振动数据模态应变能遗传算法优化;

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