Frequency response function based damage identification using principal component analysis and pattern recognition technique

Bandara, Rupika P; Chan, Tommy H.T.; Thambiratnam, David

doi:10.1016/j.engstruct.2014.01.044

Cited by 127 publications

(45 citation statements)

References 37 publications

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“…4 By definition, the Principal Components (PCs) are the eigenvalues and associated eigenvectors (principal loadings) of the covariance matrix:…”

Section: Principal Component Analysismentioning

confidence: 99%

“…Unfortunately, these experimental techniques may be difficult, costly and unreliable, because damage location must be known in advance, or it is often necessary to expose the structural elements to the inspector and the equipment for detecting damage, with relevant accessibility problems. This is the reason for which the recent decades alternative approaches, is mainly based on the changes of the vibration characteristics or response of the structures caused by a structural damage and has received considerable attention in the literature [4][5][6][7]. For example, some authors have localized damage by comparing identified mode shapes or their second-order derivatives [8] in varying levels of damage.…”

Section: Introductionmentioning

confidence: 99%

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A Comparison of Some Methods for Structural Damage Detection

2017

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In principal, a proper analysis of the dynamic response of a structure can provide general indicators of its operational conditions. When the dynamic response changes due to a variation of the physical properties of a structure, then one may conclude that some kind of damages has occurred. This paper presents investigation of the robustness and comparison of four simple methodologies to both identify and quantify the damages in structures, based on the use of Frequency Response Functions (FRF) signals, Principal Component Analysis technique (PCA) and Transmissibility. A steel beam with constant rectangular crosssection is used to compare the proposed approaches. At first, nine damaged scenarios are created and for each of them numerical examples are discussed; a database of FRFs is measured using modal testing. Then, PCA theory is applied to the FRF matrix and global damage detection and quantification indices are defined by using the first 3 Principal Components; Hotelling's T-squared distribution is also applied and by using transmissibility two other indicators, Transmissibility Damage Indicator and Weighted Damage Indicator, are computed for the assessment of damage. The reported examples show that all proposed methods are able to detect and quantify damages at the initial stage.

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“…4 By definition, the Principal Components (PCs) are the eigenvalues and associated eigenvectors (principal loadings) of the covariance matrix:…”

Section: Principal Component Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comparison of Some Methods for Structural Damage Detection

2017

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“…In the present IDE, the segmented function is utilized as the adaptive scaling factor provided in Eq. (19). …”

Section: Improved Differential Evolution Algorithmmentioning

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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“…They may also be identified regarding magnitude and phase. Besides, it also covers the data of both natural frequencies and mode shapes [3], [9], [10]. This paper presents a damage detection method using a vibration based damage detection method based on the frequency response function (FRF) data.…”

Section: Introductionmentioning

confidence: 99%

Identification of damage based on frequency response function (FRF) data

et al. 2016

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Abstract. Mechanical joints, particularly fasteners such as bolted joints have a complex non-linear behaviour. The non-linearity might emerge from the material, geometry or by the contacts in the joints. However, damage to a structure can be happened either their connections or the material of components. The effect of damage can change the dynamic properties of the structure such as natural frequencies and mode shapes and structural performance and can cause premature failure to structure. This paper presents a damage detection method using a vibration based damage detection method based on the frequency response function (FRF) data. A combination of numerical model and physical bolted jointed structure of damaged and undamaged structure will be investigated. The validation is employed to detect the presence of damage in the structure based on the frequency response function (FRF) data from the parameter values used in the benchmark model and damaged model. The comparisons of the undamaged and damaged structure of the FRF have revealed the damaged structure was shifted from the undamaged structure. The effect of the FRF between undamaged and damaged structure is clearly affected by the reduction of stiffness for the damaged structure.

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Frequency response function based damage identification using principal component analysis and pattern recognition technique

Cited by 127 publications

References 37 publications

A Comparison of Some Methods for Structural Damage Detection

A Comparison of Some Methods for Structural Damage Detection

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

Identification of damage based on frequency response function (FRF) data

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