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A Novel Optimization Algorithm Based on Modal Force Information for Structural Damage Identification
International Journal of Structural Stability and Dynamics ( IF 3.0 ) Pub Date : 2021-04-17 , DOI: 10.1142/s0219455421501005
Seyed Bahram Beheshti Aval 1 , Pooya Mohebian 1
Affiliation  

This paper proposes a novel optimization algorithm called modal force information-based optimization (MFIBO) to identify the location and severity of damage in structures. The main idea behind the MFIBO is to take advantage of information captured from the modal force of structural elements to seek the optimum damage variables. The modal element force, defined as the internal element force caused by the action of mode shapes, allows the MFIBO to recognize promising directions in the search space and assists in accelerating the optimization process. Indeed, unlike meta-heuristic optimization algorithms, which disregard explicit information about the problem and rely only upon time-consuming stochastic search computations, the MFIBO employs an informed search strategy to perform optimization in a rational and directed manner. In order to assess the effectiveness and applicability of the proposed MFIBO algorithm, four benchmark damage identification examples of truss and frame structures are conducted under both noise-free and noisy conditions. In each example, the results of the MFIBO are also compared with those attained by two well-known meta-heuristic algorithms, namely the differential evolution and the teaching–learning-based optimization. The obtained results reveal that the MFIBO is able to accurately and reliably identify structural damage with a significantly lower computational burden compared to the meta-heuristic algorithms.

中文翻译:

一种基于模态力信息的结构损伤识别优化算法

本文提出了一种新的优化算法,称为基于模态力信息的优化 (MFIBO),以识别结构中损坏的位置和严重程度。MFIBO 背后的主要思想是利用从结构元件的模态力中获取的信息来寻找最佳损伤变量。模态单元力,定义为由模态形状作用引起的内部单元力,允许 MFIBO 在搜索空间中识别有希望的方向,并有助于加速优化过程。实际上,与元启发式优化算法不同,它忽略有关问题的显式信息并且仅依赖于耗时的随机搜索计算,MFIBO 采用明智的搜索策略以理性和直接的方式执行优化。为了评估所提出的 MFIBO 算法的有效性和适用性,在无噪声和有噪声条件下进行了四个基准的桁架和框架结构损伤识别示例。在每个示例中,还将 MFIBO 的结果与两种著名的元启发式算法(即差分进化和基于教学的优化)所获得的结果进行了比较。所获得的结果表明,与元启发式算法相比,MFIBO 能够以显着降低的计算负担准确可靠地识别结构损伤。还将 MFIBO 的结果与两种著名的元启发式算法(即差分进化和基于教学的优化)所获得的结果进行了比较。所获得的结果表明,与元启发式算法相比,MFIBO 能够以显着降低的计算负担准确可靠地识别结构损伤。还将 MFIBO 的结果与两种著名的元启发式算法(即差分进化和基于教学的优化)所获得的结果进行了比较。所获得的结果表明,与元启发式算法相比,MFIBO 能够以显着降低的计算负担准确可靠地识别结构损伤。
更新日期:2021-04-17
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