Structural Damage Detection Using Localized Flexibilities

Park, K. C.; Reich, Gregory W.; Alvin, K. F.

doi:10.1177/1045389x9800901107

Cited by 33 publications

(41 citation statements)

References 11 publications

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“…A particular restriction on this method is that it requires the physically-based normalization of the damped modal coordinates as detailed in (57) and (58). This in turn requires driving point measurements (i.e.…”

Section: A Symmetrical Cbsi Methodsmentioning

confidence: 99%

Structural system identification: from reality to models

Alvin

Robertson

Reich

et al. 2003

Computers & Structures

126

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Section: A Symmetrical Cbsi Methodsmentioning

confidence: 99%

Structural system identification: from reality to models

Alvin

Robertson

Reich

et al. 2003

Computers & Structures

126

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“…The new individual by the crossover operation G ji u , can be expressed in the form: (16) where CR is the crossover rate, which is the another control parameter in the DE because it determines the probability of the middle individuals to replace the candidate individuals G i U , .Namely, the higher is the CR , the faster the update speed is.…”

Section: Crossovermentioning

confidence: 99%

“…1-5. More study efforts had been implemented based on frequency change-based method 6,7 , mode shape change-based method [8][9][10] , frequency and mode shape change-based method 11 , mode shape curvature 12,13 , modal strain enery 14,15 , flexibility based approach 16,17 , and frequency response function [18][19] .…”

Section: Introductionmentioning

confidence: 99%

Multi-stage method to identify structural damage using multiple damage location assurance criterion and an improved differential evolution algorithm

Wu¹,

Liu²,

Qin³

et al. 2017

IJCIS

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For the damage identification technique of civil structures, the reduction of the computational cost for methods based on the optimization algorithms is the most crucial step. In this study, a fast multi-stage method is developed that uses the multiple damage location assurance criterion and an improved differential evolution algorithm. In the new method, the suitable damage range is selected in different stages to reduce the computational cost of structural analysis. Five mutation operators are analysized not only in the basic differential evolution algorithm but also in the improved one. A new adaptive scaling factor with a segmented function is proposed which can operate the decay rate to avoid the premature phenomenon. The results of the study show that the precise locations and extents of structural damage are successfully realized. It is also shown that the multi-stage method using the improved differential evolution algorithm is substantially faster as compared to the basic one and can be used as an efficient and powerful measure of structural damage identification.

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“…Yun and Lee [15] applied the sequential prediction error method to estimate unknown parameters of each substructure with noisy measurements. Park et al [16] proposed structural damage identification methods based on the relative changes in localized flexibility properties, which are obtained either by applying a decomposition procedure to an experimentally determined global flexibility matrix or by processing the output signals of a vibration test in a substructure-by-substructure manner. Tee et al [17] proposed a substructure identification method considering both first-order and second-order models.…”

Section: Introductionmentioning

confidence: 99%

A Substructural Damage Identification Approach for Shear Structure Based on Changes in the First AR Model Coefficient Matrix

Liu

Mita

Zhou

2015

Journal of Structures

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A substructural damage identification approach based on changes in the first AR model coefficient matrix is proposed in this paper to identify structural damage including its location and severity. Firstly, a substructure approach is adopted in the procedure to divide a complete structure into several substructures in order to significantly reduce the number of unknown parameters for each substructure so that damage identification processes can be independently conducted on each substructure. To establish a relation between changes in AR model coefficients and structural damage for each substructure, a theoretical derivation is presented. Thus the accelerations are fed into ARMAX models to determine the AR model coefficients for each substructure under undamaged and various damaged conditions, based on which changes in the first AR model coefficient matrix (CFAR) is obtained and adopted as the damage indicator for the proposed substructure damage identification approach. To better assess the performance of the proposed procedure, a numerical simulation and an experimental verification of the proposed approach are then carried out and the results show that the proposed procedure can successfully locate and quantify the damage in both simulation and laboratory experiment.

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Structural Damage Detection Using Localized Flexibilities

Cited by 33 publications

References 11 publications

Structural system identification: from reality to models

Structural system identification: from reality to models

Multi-stage method to identify structural damage using multiple damage location assurance criterion and an improved differential evolution algorithm

A Substructural Damage Identification Approach for Shear Structure Based on Changes in the First AR Model Coefficient Matrix

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