Model-Free Method for Damage Localization of Grid Structure

Yang, Qiuwei; Wang, Chaojun; Li, Na; Luo, Shijian; Wang, Wei

doi:10.3390/app9163252

Cited by 3 publications

(2 citation statements)

References 17 publications

(20 reference statements)

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“…Using flexibility disassembly perturbation, Yang and Sun [4][5][6] proposed a fast analysis method for the static displacement for structural damage detection. Using the static strain change, Yang et al [7] developed a model-free method for damage localization for a grid structure. Bakhtiari-Nejad et al [8] developed non-linear equations that relate static response variations to fault location and extent.…”

Section: Introductionmentioning

confidence: 99%

Structural Fault Diagnosis Based on Static and Dynamic Response Parameters

2023

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Structural fault diagnosis is an important subject for ensuring the normal use of structures. More test data will help to improve the accuracy and reliability of structural fault diagnosis. Therefore, a structural fault detection algorithm based on static–dynamic mixed sensitivity analysis is proposed. The vibration parameters used were the vibration modes of some of the nodes in the structure measured by the vibration test system. The static response parameter used was the vertical displacement of the structure under the gravity load measured by the static test system. In particular, the gravity load and the structure were connected rigidly to form a new added-mass system. The vibration mode of the additional-mass system was measured again to obtain more equations for fault evaluation. Based on the static and dynamic measurement data, the failure coefficients of all components in the structure were calculated through the mixed sensitivity of the static displacement and vibration-mode shape. According to the calculated value of the failure coefficient, the failure state of all components in the structure could be finally evaluated. The main innovation of the proposed method was the use of the static load as a part of the new added-mass system to obtain more vibration parameters for the defect diagnosis. The implementation process and effect of this method were verified using a numerical truss structure and an experimental steel beam structure. Moreover, the defect diagnosis results of the proposed hybrid method were compared with those of a pure static algorithm and a pure dynamic algorithm to illustrate the advantages of the hybrid method. The research results showed that this method has the advantages of simple implementation and high diagnosis accuracy. Especially for symmetric structures, the proposed method can successfully avoid the possible missed diagnoses of the pure static algorithm and pure dynamic method. The algorithm provides a simple and feasible method for structural defect identification.

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Section: Introductionmentioning

confidence: 99%

Structural Fault Diagnosis Based on Static and Dynamic Response Parameters

2023

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“…For the purpose of fully utilized mode information, Kaouk and Zimmerman [14][15][16] defined the residual mode equation for damage detection based on mode information of structure, which can accomplish the dual tasks of determining the damage location and solving the damage situation effectively. is kind of damage detection method has received the widespread attention over the last decade [17][18][19][20][21]. ere exists a common obstacle in the aforementioned detection methods, which is to obtain higher order of structural modal shapes.…”

Section: Introductionmentioning

confidence: 99%

Residual Mode Vector‐Based Structural Damage Identification with First‐Order Modal Information

Luo

Zhuang

Wang

et al. 2021

Advances in Materials Science and Engineering

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Damage identification based on the change of dynamic properties is an issue worthy of attention in structure safety assessment, nevertheless, only a small number of discontinuous members in existing structure are damaged under service condition, and the most remaining members are in good condition. According to this feather, we developed an effective damage location and situation assessment algorithm based on residual mode vector with the first mode information of targeted structure, which utilized the quantitative relationship between first natural modes of global structure with the change of the element stiffness. Firstly, the element damage location is determined with exploitation of the sparseness of element stiffness matrices based on the discontinuity of damaged members. Then, according to the distribution characteristics of the corresponding residual mode vector, the nodal equilibrium equation about the damage parameter is established based on the residual mode vector, and the damage coefficients of structural elements are evaluated with the proposed equations. Two numerical examples are given to verify the proposed algorithm. The results showed that the proposed damage identification method is consistent with the preset damage. It can even accurately identify large-degree damages. The proposed algorithm only required the first-order modal information of the target structures and held few requirements of analysis resource; hence when compared with existing methods, it has obvious advantages for structural damage identification.

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A Comparative Study of the Data-Driven Stochastic Subspace Methods for Health Monitoring of Structures: A Bridge Case Study

Shokravi

Bakhary

et al. 2020

Applied Sciences

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Subspace system identification is a class of methods to estimate state-space model based on low rank characteristic of a system. State-space-based subspace system identification is the dominant subspace method for system identification in health monitoring of the civil structures. The weight matrices of canonical variate analysis (CVA), principle component (PC), and unweighted principle component (UPC), are used in stochastic subspace identification (SSI) to reduce the complexity and optimize the prediction in identification process. However, researches on evaluation and comparison of weight matrices’ performance are very limited. This study provides a detailed analysis on the effect of different weight matrices on robustness, accuracy, and computation efficiency. Two case studies including a lumped mass system and the response dataset of the Alamosa Canyon Bridge are used in this study. The results demonstrated that UPC algorithm had better performance compared to two other algorithms. It can be concluded that though dimensionality reduction in PC and CVA lingered the computation time, it has yielded an improved modal identification in PC.

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Model-Free Method for Damage Localization of Grid Structure

Cited by 3 publications

References 17 publications

Structural Fault Diagnosis Based on Static and Dynamic Response Parameters

Structural Fault Diagnosis Based on Static and Dynamic Response Parameters

Residual Mode Vector‐Based Structural Damage Identification with First‐Order Modal Information

A Comparative Study of the Data-Driven Stochastic Subspace Methods for Health Monitoring of Structures: A Bridge Case Study

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