A multistage FE updating procedure for damage identification in large-scale structures based on multiobjective evolutionary optimization

Perera, Ricardo; Ruíz, Antonio

doi:10.1016/j.ymssp.2007.10.004

Cited by 167 publications

(87 citation statements)

References 30 publications

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“…For the application in structure damage detection, Jaishi and Ren [147] used a multi-objective optimization technique to optimize two objective functions simultaneously, which overcomes the difficulty of weighing the individual objective function in conventional FE model updating procedure. Perera et al [143,193,194] developed an evolutionary (GA and PSO) multi-objective framework for structural damage localization and quantification with objective functions based on the modal flexibilities, frequencies, and modal shapes. Cha and Buyukozturk [195] proposed hybrid multi-objective optimization algorithms based on modal strain energy to detect damages in various three-dimensional steel structures.…”

Section: Multi-objective Optimization Algorithmsmentioning

confidence: 99%

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

2017

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Abstract:Research on detecting structural damage at the earliest possible stage has been an interesting topic for decades. Among them, the vibration-based damage detection method as a global technique is especially pervasive. The present study reviewed the state-of-the-art on the framework of vibration-based damage identification in different levels including the prediction of the remaining useful life of structures and the decision making for proper actions. This framework consists of several major parts including the detection of damage occurrence using response-based methods, building reasonable structural models, selecting damage parameters and constructing objective functions with sensitivity analysis, adopting optimization techniques to solve the problem, predicting the remaining useful life of structures, and making decisions for the next actions. For each part, the commonly used methods were reviewed and the merits and drawbacks were summarized to give recommendations. This framework is aimed to guide the researchers and engineers to implement step by step the structure damage identification using vibration measurements. Finally, the future research work in this field is recommended.

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Section: Multi-objective Optimization Algorithmsmentioning

confidence: 99%

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

2017

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“…GA was applied to a simulated beam, as well as a frame structure using frequencies and MAC-based objective functions to efficiently detect damage [16,17]. Multiobjective GA was also used to detect damage in a simulated beam and signature bridge structure based on MAC and flexibility-based objective functions [21]. However, due to the simplification of a 3D model to a 2D model, the first three vertical modes were matched, and torsional modes were not included in model updating.…”

Section: Introductionmentioning

confidence: 99%

Structural Damage Detection with Different Objective Functions in Noisy Conditions Using an Evolutionary Algorithm

et al. 2017

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Dynamic properties such as natural frequencies and mode shapes are directly affected by damage in structures. In this paper, changes in natural frequencies and mode shapes were used as the input to various objective functions for damage detection. Objective functions related to natural frequencies, mode shapes, modal flexibility and modal strain energy have been used, and their performances have been analyzed in varying noise conditions. Three beams were analyzed: two of which were simulated beams with single and multiple damage scenarios and one was an experimental beam. In order to do this, SAP 2000 (v14, Computers and Structures Inc., Berkeley, CA, United States, 2009) is linked with MATLAB (r2015, The MathWorks, Inc., Natick, MA, United States, 2015). The genetic algorithm (GA), an evolutionary algorithm (EA), was used to update the damaged structure for damage detection. Due to the degradation of the performance of objective functions in varying noisy conditions, a modified objective function based on the concept of regularization has been proposed, which can be effectively used in combination with EA. All three beams were used to validate the proposed procedure. It has been found that the modified objective function gives better results even in noisy and actual experimental conditions.

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“…The most common modal data applied are natural frequencies and modal shapes [14][15][16][17][18][19][20][21][22][23][24].…”

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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A multistage FE updating procedure for damage identification in large-scale structures based on multiobjective evolutionary optimization

Cited by 167 publications

References 30 publications

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

Structural Damage Detection with Different Objective Functions in Noisy Conditions Using an Evolutionary Algorithm

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

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