Structural crack detection without updated baseline model by single and multiobjective optimization

Perera, Ricardo; Fang, Sheng-En; Huerta, Consuelo

doi:10.1016/j.ymssp.2008.06.010

Cited by 37 publications

(20 citation statements)

References 23 publications

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“…[10][11][12] The general noniterative two-stage approach (non-ITSA) has been extensively investigated over the past few years. Several effective modal strain energy-based methods, 8 metaheuristic optimization algorithms, [9][10][11][12][13] and objective functions 14,15 have been introduced, all of which greatly improved the damage localization and severity estimation precision. However, several problems must still be resolved.…”

Section: Introductionmentioning

confidence: 99%

Iterative two-stage approach for identifying structural damage by combining the modal strain energy decomposition method with the multiobjective particle swarm optimization algorithm

Wang

Jiang

2018

Struct Control Health Monit

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Summary An iterative two‐stage structural damage identification approach that combines the modal strain energy decomposition (MSED) method with the multiobjective particle swarm optimization algorithm is presented. The proposed scheme is inspired by the general noniterative two‐stage approach, which attempts to locate damage in the first stage and estimate the severity of damage in the second stage; however, the present approach differs by constructing an iterative MSED indicator to perform damage localization and severity estimation in a cyclic manner. Consequently, false positive indications of damage are gradually suppressed, and the precision of the damage severity estimation is improved as the iteration continues. In addition, a new element activation operation is embedded into the iterative process; in this step, possible false negative indications of damage excluded in the first stage can be activated and subsequently retested to identify damage, thereby reducing the false negative rate. Furthermore, a comparative study is conducted between the iterative two‐stage approach and the general noniterative approach by contemplating a 3‐D structure, and the effects of measurement noise and spatial incompleteness are considered.

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Section: Introductionmentioning

confidence: 99%

Iterative two-stage approach for identifying structural damage by combining the modal strain energy decomposition method with the multiobjective particle swarm optimization algorithm

Wang

Jiang

2018

Struct Control Health Monit

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“…So as to use the benefits from both natural frequencies and mode shapes simultaneously, Perera et al [34] recruit a combination of natural frequencies and mode shapes of the structure in a multi-objective framework to construct an objective function for damage detection. Instead of directly using these parameters, they make use of their differences in the objective function.…”

Section: Introductionmentioning

confidence: 99%

Modal Data Based Approach for Structural Damage Identification by Means of Imperialist Competitive Optimization Algorithm

2017

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In this paper, an effective method for structural damage detection is put forth in which an objective function based on the natural frequencies and modal shapes of the structure is established to identify and detect structural damage. The problem is defined and solved as an optimization problem employing Imperialist Competition Algorithm (ICA). Moreover, four numerical examples are examined each of which has different damage scenarios in order that the applicability of the method would be clearly proved. The results show the efficiency of the method in detecting single and multiple damages in different structures. Afterwards, the effects of measurement noises are included in some of the examples so that the method can be more consistent with real situations. Besides, a comparison among several evolutionary optimization algorithms in the research is made to enlighten the accuracy, robustness and reliability of the method. All of the results lead to the conclusion that the suggested method of the paper is of good accuracy, and, therefore, can be both used and trusted in solving damage detection problems, even in cases that measurement noises are encountered.

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“…Another set of structural damage detection methods employs an optimization basis for solving the damage identification problem (Chou and Ghaboussi 2001;Perera and Torres 2006;Perera, Fang, and Huerta 2009;Meruane and Heylen 2011;Bagheri, Razeghi, and Ghodrati Amiri 2012;Kourehli et al 2012;Perera, Marina, and Ruiz 2013;Saada, Arafa, and Nassef 2013). Teughels and De Roeck (2005) defined the damage identification procedure by a finite element model updating scheme and solved this problem by combining two traditional optimization algorithms.…”

Section: Introductionmentioning

confidence: 99%

Optimization-based method for structural damage localization and quantification by means of static displacements computed by flexibility matrix

Hosseinzadeh

Amiri

Koo

2015

Engineering Optimization

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This article presents an effective method for structural damage identification. The damage diagnosis problem is introduced as an optimization problem which is based on computing static displacements by the flexibility matrix. By utilizing this matrix, the complexity of the static displacement measurements in real cases can be overcome. The optimization problem is solved by a fast evolutionary optimization strategy, named the cuckoo optimization algorithm. The performance of the presented method was demonstrated by studying the benchmark problem provided by the IASC-ASCE Task Group on Structural Health Monitoring, and a numerical example of a frame. Moreover, the robustness of the presented approach was investigated in the presence of some prevalent modelling errors, and also when noisy and incomplete modal data are available. Finally, the efficiency of the proposed method was verified by an experimental study of a five-storey shear building structure. All the obtained results show the good performance of the presented method.

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Structural crack detection without updated baseline model by single and multiobjective optimization

Cited by 37 publications

References 23 publications

Iterative two-stage approach for identifying structural damage by combining the modal strain energy decomposition method with the multiobjective particle swarm optimization algorithm

Iterative two-stage approach for identifying structural damage by combining the modal strain energy decomposition method with the multiobjective particle swarm optimization algorithm

Modal Data Based Approach for Structural Damage Identification by Means of Imperialist Competitive Optimization Algorithm

Optimization-based method for structural damage localization and quantification by means of static displacements computed by flexibility matrix

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