Damage assessment in structures using combination of a modified Cornwell indicator and genetic algorithm

Tiachacht, Samir; Bouazzouni, A.; Khatir, Samir; Wahab, Magd Abdel; Behtani, A.; Capozucca, Roberto

doi:10.1016/j.engstruct.2018.09.070

Cited by 108 publications

(37 citation statements)

References 44 publications

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“…A disadvantage, for example, is that they require great calculation effort. [8] Some of the recent damage detection studies have been conducted using GA. For instance, Tiachacht et al [9] have introduced a new identification technique for 2D and 3D structures, using GA and modified Cornwell indicator (MCI). In their paper, an objective function based on MCI is defined for damage detection and severity identification for structural elements based on modal information of damaged structures.…”

Section: Introductionmentioning

confidence: 99%

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

Ghannadi

Kourehli

2020

Structural Design Tall Build

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New optimization algorithms have been increasingly developed in the course of the recent years. The accuracy of identified results in optimization-based damage detection methods depends on the objective function and optimization algorithm. This paper employs multiverse Optimizer (MVO) to solve the optimization-based damage identification problem. Statistical results obtained by MVO are compared with those of sine cosine algorithm (SCA) and Harris hawks optimization (HHO) in order to perform a comparative study. Two objective functions are used in this optimization problem. The first one is based on the modal assurance criterion (MAC) and the second one on modified total modal assurance criterion (MTMAC). Numerical and experimental examples indicate that the combination of objective function based on MTMAC and MVO algorithm can provide accurate and reliable results in structural damage detection process. MAC is also rejected in competition with MTMAC. While using SCA-MTMAC, the accuracy of the results is acceptable in some cases. However, HHO-MTMAC gives weak results in most cases. MVO and SSA are the lowest, and HHO spends significantly more time in terms of computational cost.

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Section: Introductionmentioning

confidence: 99%

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

Ghannadi

Kourehli

2020

Structural Design Tall Build

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“…They solve an inverse problem by building a physics-based model and then updating its parameters until the response of the model matches that which is measured in the real structure. Although this approach is currently under exhaustive research [19][20][21][22][23][24][25], it still presents some drawbacks in the assessment of real systems. Such drawbacks include the need for high-quality data and the impossibility to provide real-time insight due to the computational effort required to solve the updating problem [26].…”

Section: Introductionmentioning

confidence: 99%

Bearing assessment tool for longitudinal bridge performance

Fernández-Navamuel

Zamora-Sánchez

Alvear

et al. 2020

J Civil Struct Health Monit

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This work provides an unsupervised learning approach based on a single-valued performance indicator to monitor the global behavior of critical components in a viaduct, such as bearings. We propose an outlier detection method for longitudinal displacements to assess the behavior of a singular asymmetric prestressed concrete structure with a 120 m high central pier acting as a fixed point. We first show that the available long-term horizontal displacement measurements recorded during the undamaged state exhibit strong correlations at the different locations of the bearings. Thus, we combine measurements from four sensors to design a robust performance indicator that is only weakly affected by temperature variations after the application of principal component analysis. We validate the method and show its efficiency against false positives and negatives using several metrics: accuracy, precision, recall, and F1 score. Due to its unsupervised learning scope, the proposed technique is intended to serve as a real-time supervision tool that complements maintenance inspections. It aims to provide support for the prioritization and postponement of maintenance actions in bridge management.

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“…Kaveh and Dadras [20] enhanced Thermal Exchange Optimization (TEO) and applied for structural damage detection. Tiachacht et al [21] presented a new methodology based on model updating method for damage identification and quantification of two-and three-dimensional structures using the Genetic Algorithm (GA). Jahangiri et al [22] presented an efficient damage detection technique based on a hybrid objective function and using the only first vibration mode data utilizing meta-heuristic optimization algorithms.…”

Section: Introductionmentioning

confidence: 99%

Boundary Strategy for Optimization-based Structural Damage Detection Problem using Metaheuristic Algorithms

Kaveh

Hosseini

Zaerreza

2020

Period. Polytech. Civil Eng.

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The present paper proposes a new strategy namely Boundary Strategy (BS) in the process of optimization-based damage detection using metaheuristic algorithms. This strategy gradually neutralizes the effects of structural elements that are healthy in the optimization process. BS causes the optimization method to find the optimum solution better than conventional methods that do not use the proposed BS. This technique improves both aspects of the accuracy and convergence speed of the algorithms in identifying and quantifying the damage. To evaluate the performance of the developed strategy, a new damage-sensitive cost function, which is defined based on vibration data of the structure, is optimized utilizing the Shuffled Shepherd Optimization Algorithm (SSOA). Different examples including truss, beam, and frame are investigated numerically in order to indicate the applicability of the proposed technique. The proposed approach is also applied to other well-known optimization algorithms including TLBO, GWO, and MFO. The obtained results illustrate that the proposed method improves the performance of the utilized algorithms in identifying and quantifying of the damaged elements, even for noise-contaminated data.

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Damage assessment in structures using combination of a modified Cornwell indicator and genetic algorithm

Cited by 108 publications

References 44 publications

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

Multiverse optimizer for structural damage detection: Numerical study and experimental validation

Bearing assessment tool for longitudinal bridge performance

Boundary Strategy for Optimization-based Structural Damage Detection Problem using Metaheuristic Algorithms

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