A review on dynamic substructuring methods for model updating and damage detection of large-scale structures

Weng, Shun; Zhu, Hongping; Xia, Yong; Li, Jiajing; Tian, Weisheng

doi:10.1177/1369433219872429

Cited by 50 publications

(25 citation statements)

References 102 publications

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“…To reduce iteration times and increase computation efficiency, substructure techniques have been developed [28][29][30][31][32][33][34][35]. It divided the whole structures into several small substructures, each of which was treated independently.…”

Section: Frequencies and Mode Shapesmentioning

confidence: 99%

Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes

2021

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Structural damages occur in modern structures during operations due to environmental and human factors. The damages accumulating with time may lead to a significant decrease in structure performance or even destruction; natural symmetry is broken, resulting in an unexpected life and economic loss. Therefore, it is necessary to monitor the structural response to detect the damage in an early stage, evaluate the health condition of structures, and ensure the operation safety of structures. In fact, the structure and the evaluation can be considered as a special symmetry. Among several SHM methods, vibration-based SHM techniques have been widely adopted recently. Hence, this paper reviews the vibration-based SHM methods in terms of the vibrational parameters used. In addition, the technical codes on vibration based SHM system have also been reviewed, since they are more important in engineering applications. Several related ISO standards and national codes have been developed and implemented, while more specific technical codes are still required to provide more detailed guidelines in practice to maintain structure safety and natural symmetry.

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Section: Frequencies and Mode Shapesmentioning

confidence: 99%

Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes

2021

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“…It is possible to detect the beginning of a possible damage/failure in a structure and its components using methods associated with SHM systems [ 1 ]. Damage identification includes several levels including damage detection [ 2 , 3 ]. However, disturbances for robust damage identification need to be considered using algorithms for data-driven strategies [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Structural Damage Classification in a Jacket-Type Wind-Turbine Foundation Using Principal Component Analysis and Extreme Gradient Boosting

Leon-Medina

Anaya

Mariné

et al. 2021

Sensors

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Damage classification is an important topic in the development of structural health monitoring systems. When applied to wind-turbine foundations, it provides information about the state of the structure, helps in maintenance, and prevents catastrophic failures. A data-driven pattern-recognition methodology for structural damage classification was developed in this study. The proposed methodology involves several stages: (1) data acquisition, (2) data arrangement, (3) data normalization through the mean-centered unitary group-scaling method, (4) linear feature extraction, (5) classification using the extreme gradient boosting machine learning classifier, and (6) validation applying a 5-fold cross-validation technique. The linear feature extraction capabilities of principal component analysis are employed; the original data of 58,008 features is reduced to only 21 features. The methodology is validated with an experimental test performed in a small-scale wind-turbine foundation structure that simulates the perturbation effects caused by wind and marine waves by applying an unknown white noise signal excitation to the structure. A vibration-response methodology is selected for collecting accelerometer data from both the healthy structure and the structure subjected to four different damage scenarios. The datasets are satisfactorily classified, with performance measures over 99.9% after using the proposed damage classification methodology.

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“…Vibration-based structural damage identification methods have been obtained and widely used in various civil engineering examples [9,10], which provide a possible solution to the bearing damage detection. Chen et al [11] investigated the feasibility and sensitivity of bearing damage identification using bridge vibration modes and the radial basis function neural network; the results indicate that modal information can reflect the bearing damage clearly.…”

Section: Introductionmentioning

confidence: 99%

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Lei

Zhou

et al. 2021

Shock and Vibration

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The bearing of a bridge, as a critical component, is important in the force transformation of the superstructure; however, due to the service condition and repeated impact load, the bearing is prone to be damaged but difficult to detect the damage; the present research has few studies that focused on the damage detection of the structural bearing. Meanwhile, practical engineering is always surrounded by variational environmental conditions, and sometimes, the element and bearing damage both exist in the structure. Thus, these uncertain conditions all cause inaccurate damage identification results using the vibration-based damage detection method. In order to detect the damage of the structural bearing and improve the precision, firstly, the structural dynamic characteristic equation considering uncertain conditions has been deduced; then, a damage detection framework constructed by the Bayesian theory and perturbation method has been developed in this article; a numerical example of an 8-span concrete continuous beam and a practical example of I-40 steel-concrete composite bridge are utilized to validate the feasibility of the proposed method, and single type and two types of damage cases are studied. The outcomes demonstrate that the damage of structural elements and bearings can be detected with high accuracy. The proposed method is of great applicability and good potential.

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A review on dynamic substructuring methods for model updating and damage detection of large-scale structures

Cited by 50 publications

References 102 publications

Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes

Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes

Structural Damage Classification in a Jacket-Type Wind-Turbine Foundation Using Principal Component Analysis and Extreme Gradient Boosting

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

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