Structural Damage Identification Using an Adaptive Multi-stage Optimization Method Based on a Modified Particle Swarm Algorithm

Shirazi, Mojtaba; Mollamahmoudi, H.; Seyedpoor, S. M.

doi:10.1007/s10957-013-0316-6

Cited by 35 publications

(21 citation statements)

References 9 publications

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“…Subsequently, the MSEBI was further used by Kaveh and Zolghadr to develop another two‐stage method. Similar work can be found in the literature …”

Section: Introductionsupporting

confidence: 84%

“…The general non‐ITSA attempts to establish the location of damage by utilizing a damage localization technique in the first stage and to subsequently estimate the severity of damage by employing a metaheuristic optimization algorithm in the second stage. The formulation of the non‐ITSA varies, as can be found in published papers . To develop the non‐ITSA in this paper, the MSED method is selected as the damage localization technique, and the MOPSO algorithm is selected as the method to estimate the damage severity.…”

Section: The General Non‐itsamentioning

confidence: 99%

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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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“…Subsequently, the MSEBI was further used by Kaveh and Zolghadr to develop another two‐stage method. Similar work can be found in the literature …”

Section: Introductionsupporting

confidence: 84%

Section: The General Non‐itsamentioning

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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“…Qian proposed a hybrid optimization algorithm based on particle swarm optimization to identify the layered damage in the composite structure [6] . Shirazi proposed an adaptive multi-level optimization method based on particle swarm optimization algorithm to identify multiple damage of structure [7] . However, when the PSO algorithm is used to identify the structural damage, the small damage will be neglected due to the interference of the adjacent units.…”

Section: Introductionmentioning

confidence: 99%

Structural Damage Identification Based on Wavelet Analysis and Particle Swarm Optimization

Guan¹,

Liu²,

Wang³

2018

Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017)

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Abstract. In order to identify the multiple damage of the structure, this paper presents a method of structural damage identification based on wavelet analysis and particle swarm optimization(PSO). Firstly, analyzing dynamic characteristics of the finite element model to obtain the strain mode, then continuous wavelet transform is carried out for the strain mode, and the damage location of the structure is identified according to the modulus maximum of the wavelet coefficient, on this basis, using the natural frequency and the vibration mode before and after the structural damage construct the objective function, and then using PSO algorithm optimize the objective function to obtain the damage degree of the structure. Finally, a numerical example is given to demonstrate the effectiveness of this method in identifying structural damage.

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“…Although their method seems effective, there are discrepancies in the approximations made for the damaged elements; more precisely, damage is not exactly determined. Later on, utilizing the first few natural frequencies as the main parameters of the objective function and benefiting from Multi-stage PSO as the optimizer to solve the inverse problem, a new damage detection method was proposed in [35]. In [36] an objective function based on natural frequencies and modal shapes of the structure is defined via the Modal Assurance Criterion where the inverse optimization problem is solved via employing a fusion of the GA and PSO.…”

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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Structural Damage Identification Using an Adaptive Multi-stage Optimization Method Based on a Modified Particle Swarm Algorithm

Cited by 35 publications

References 9 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

Structural Damage Identification Based on Wavelet Analysis and Particle Swarm Optimization

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

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