A new iterative model updating method using incomplete frequency response function data

Gang, Xianyue; Chai, Senchun; Allemang, Randall J.; Li, Lijun

doi:10.1016/j.jsv.2013.12.008

Cited by 33 publications

(9 citation statements)

References 6 publications

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“…Gang et al . developed a method based on a vector of discrepancy between analytical and experimental FRF data obtained from measured data in master DOFs and estimated data in pseudo master DOFs by a reduced model iteratively. Yuan and Yu proposed a model updating method for damped structures exposed to base excitation utilizing a complex form of transfer function.…”

Section: Introductionmentioning

confidence: 99%

Structural model updating using incomplete transfer function and modal data

Farshadi

Esfandiari

Vahedi

2016

Struct Control Health Monit

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Structural damage detection by non-destructive techniques has been investigated widely by researchers in recent years, and several response-based Structural Health monitoring techniques have been developed. In this paper, a vibration-based damage detection algorithm through model updating utilizing incomplete frequency response function and modal data is presented. First, a modified sensitivity equation is presented to relate the changes of mode shapes to the changes of unknown structural parameters. Then, the developed equations are used to correlate changes of frequency response functions to the changes of structural parameters. Parameter estimation is conducted through least square solution of sensitivity equations. In order to prove the capability of the proposed method for structural damage detection purpose, a numerical example using error contaminated data is presented. Results exhibit robustness of method against measurement and mass modeling errors. KEYWORDS damage detection, frequency response function, modified modal method, sensitivity equation | INTRODUCTIONEvery structure may experience changes in structural properties during its design life because of the occurrence of several conditions such as extreme loading, earthquake, strong wind, erosion, and fatigue. Even if a structure is managed to withstand such changes, it is crucial to investigate its integrity. To ensure this objective, many algorithms have recently been developed to detect the location and severity of structural damages and evaluation of its safety. The basic principle of damage detection algorithms is because damage can cause detectable changes in structural response.A general classification of damage identification techniques refers to types of data used to detect damage including static and dynamic data. Most common dynamic features are modal data including mode shapes, [1,2] natural frequencies, [3,4] strain energy, [5] transfer function parameters, [6] measured modal flexibility, [7,8] frequency response function (FRF), [9][10][11][12] time domain structural responses, [13][14][15] or a combination of these features. [16,17] Damage detection by model updating is the process of modification of structural parameters to minimize discrepancy between response of structure and numerical model. The response residual can be minimized by various approaches. [18][19][20] Because model updating is an inverse problem and the relationship between structural parameters and measured response is inherently nonlinear, methods known as sensitivity-based approaches are developed to simplify solving this problem through linearization of equations. [21] Model updating using FRF improves predictive capabilities of updating procedure through providing large amount of information and has been used by some researchers. [22][23][24] One of the main advantages of using FRFs data in sensitivity-based model updating algorithm is avoiding propagation of errors in parameter estimation. [25,26] By sensitivity-based approaches, FRF residual is minimized to eval...

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Section: Introductionmentioning

confidence: 99%

Structural model updating using incomplete transfer function and modal data

Farshadi

Esfandiari

Vahedi

2016

Struct Control Health Monit

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“…Sipple and Sanayei 11 proposed a new frequency response function (FRF)–based model updating method using numerical sensitivity as opposed to conventional analytical sensitivity. Gang et al 12 developed a method based on a vector of discrepancy between analytical and experimental FRF data obtained from measured data in master degrees of freedom (DOFs) and estimated data in pseudo master DOFs with a reduced model iteratively. Dos Santos et al 13 identified damage of laminated structures by a FRF sensitivity–based damage detection algorithm.…”

Section: Introductionmentioning

confidence: 99%

Application of Bayesian statistical method in sensitivity-based seismic damage identification of structures: Numerical and experimental validation

Vahedi

Khoshnoudian

Hsu

2018

Structural Health Monitoring

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Most of the developed sensitivity-based damage detection methods are based on the application of external excitations which could be prohibitive due to infeasible excitation of all structural degrees of freedom. In this regard, identification of damage properties using seismic structural response would be advantageous. In this research, sensitivity-based finite element model updating method is proposed to identify structural damage by earthquake response in the frequency domain and the transfer function of the structure due to ground excitation. The obtained sensitivity equation is solved by linear least square method through defining constraints on the design variables. Since the attainable measured data are restricted by limits on the instrumentations and preciseness of the measurements and due to the fact that only a few of the lower modes of a structure can generally be determined with confidence, a Bayesian statistical method is utilized to enhance the reliability of the predicted damage properties. The proposed technique is applied to a numerical frame model and an experimental six-story steel structure with various scenarios of story stiffness reduction. The results are indicative of the capability of the proposed method for identification of damage location and severity.

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“…A comparative study was carried out in [25] to compare the direct updating methods and the RFM, which drew the conclusion that RFM has advantage in the updating of response. Gang [26] applied dynamic reduction technique in the RFM, which enhanced the engineering application ability of the method.…”

Section: Introductionmentioning

confidence: 99%

Finite element model updating of damped structures using vibration test data under base excitation

Yuan

2015

Journal of Sound and Vibration

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A new iterative model updating method using incomplete frequency response function data

Cited by 33 publications

References 6 publications

Structural model updating using incomplete transfer function and modal data

Structural model updating using incomplete transfer function and modal data

Application of Bayesian statistical method in sensitivity-based seismic damage identification of structures: Numerical and experimental validation

Finite element model updating of damped structures using vibration test data under base excitation

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