A frequency response function change method for damage localization and quantification in a shear building under ground excitation

Hsu, Ting-Yu; Loh, Chin‐Hsiung

doi:10.1002/eqe.2235

Cited by 10 publications

(10 citation statements)

References 20 publications

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“…It is shown that the uncertainty due to nonlinear effects is hardly comprehensible in comparison with other measurement uncertainties in dynamic experiments . Some researchers developed damage detection methods with the assumption of linear elastic behavior under small ground excitations . Limongelli validated the Interpolation Damage Detecting Method neglecting the effect of nonlinear behavior .…”

Section: Proposed Methodsmentioning

confidence: 99%

“…In recent studies, it is observed that the change in the damping of a structure was quite small compared with the stiffness degradation for typical buildings and bridge structures under small excitations . Hence, it can be assumed that the damping matrix is unchanged after the system is damaged when the system remains linearly elastic under small ground excitations . In addition, due to the fact that the damping of a structure may not only relate to the material property of the elements, modeling and updating the damping may introduce significant inaccuracy into the model updating.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…For the shear building of the numerical example 3.1, the mass matrix is a diagonal matrix containing lumped mass related to each floor. The stiffness matrix is calculated similar to a typical shear building as

normalK = ([], \begin{matrix} K_{1} + K_{2} - K_{2} \begin{matrix} 0 \end{matrix} \\ \begin{matrix} - {normalK}_{2} & {normalK}_{2} + {normalK}_{3} \end{matrix} \begin{matrix} ⋱ \end{matrix} \\ \begin{matrix}  \end{matrix} \begin{matrix} ⋱ \end{matrix} \\ \begin{matrix} 0 \end{matrix} \begin{matrix} - {normalK}_{6} & {normalK}_{6} \end{matrix} \end{matrix}) .

It is assumed that the mass and damping matrices are unchanged after the system is damaged when the system remains linearly elastic under small ground excitations . For defining the structural matrices in the damaged state, it is assumed that the damage to a structure causes the degradation of its structural stiffness but without changes in the mass of the structure.…”

Section: Illustrative Examplesmentioning

confidence: 99%

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Transfer function‐based Bayesian damage detection under seismic excitation

Vahedi

Khoshnoudian

Hsu

et al. 2019

Structural Design Tall Build

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Summary Transfer function (TF) data are recognized as diagnostic features in damage detection procedure. The objective of this paper is to present a damage detection method in Bayesian paradigm based on TF data due to ground excitation. The measured seismic responses of the structure in the frequency domain are adopted to obtain displacement TFs and the structural natural frequencies are identified from observed TFs. The derived features are utilized for Bayesian structural damage detection. In addition, the challenging issue of underlying flexible soil in real cases has been addressed. The proposed technique is applied to a numerical shear frame to evaluate the capability of the method. An experimental study on a six‐story steel building has been validated to demonstrate the capability of the method for damage detection purpose. The results of studied cases indicated that the proposed method is capable of identifying the location and the severity of damage precisely.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Proposed Methodsmentioning

confidence: 99%

normalK = ([], \begin{matrix} K_{1} + K_{2} - K_{2} \begin{matrix} 0 \end{matrix} \\ \begin{matrix} - {normalK}_{2} & {normalK}_{2} + {normalK}_{3} \end{matrix} \begin{matrix} ⋱ \end{matrix} \\ \begin{matrix}  \end{matrix} \begin{matrix} ⋱ \end{matrix} \\ \begin{matrix} 0 \end{matrix} \begin{matrix} - {normalK}_{6} & {normalK}_{6} \end{matrix} \end{matrix}) .

Section: Illustrative Examplesmentioning

confidence: 99%

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Transfer function‐based Bayesian damage detection under seismic excitation

Vahedi

Khoshnoudian

Hsu

et al. 2019

Structural Design Tall Build

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“…Liu et al presented a scheme using FRF curvatures to localize damage for a simulated cantilever beam. Recently, several FRF‐based detection methods have been developed by using advanced approaches such as subspace identification algorithms, pattern recognition techniques, orthogonal matching pursuits, and signal processing techniques . The curvature‐based methods seem to be more easily implemented for practical applications in comparison with the many recently proposed approaches …”

Section: Introductionmentioning

confidence: 99%

Damage detection in shear buildings using different estimated curvature

Shi

Spencer

Chen

2017

Struct Control Health Monit

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SummaryThis study investigates the damage localization employing the curvature of the lateral displacement envelope in shear building structures. Both the finite difference method and the proposed interpolation method are applied to evaluate the curvature of mode shapes and frequency response functions (FRFs) in a 12-story shear building. The interpolated displacement function used in the proposed method considers appropriate continuity and boundary conditions for the shear buildings.Numerical studies show that using the curvature by the proposed method could reduce the occurrences of false damage localization when the vibration responses include small simulated noise. Moreover, the existing FRF curvature method could perform worse than random guessing to find correct damage locations at the cost of the considerable number of false alarms. However, the poor detection performance of the existing method may be enhanced significantly by using the proposed method to evaluate the curvature of the FRFs if the simulated noise is under a small level.The proposed method is shown to perform better than the finite difference method to improve the effectiveness of the curvature-based methods for damage detection. | INTRODUCTIONNumerous vibration-based damage detection (VBDD) methods have been developed to identify and localize damage in structures during the last few decades. VBDD methods detect and quantify the structural damage by analyzing the changes of the dynamic responses for structures. The development of VBDD methods has been reviewed in recent studies by Farrar and Worden [1] and Fan and Qiao. [2] Modal response has been frequently employed for damage detection. Several studies [3][4][5][6][7][8][9][10][11][12] investigated the changes of mode shapes between the intact and damaged states of the structure to localize and quantify the structural damage. Pandey et al. [3] first presented a method to detect damage from changes in curvature mode shapes and also indicated that the difference in a curvature mode shape between an intact and a damaged beam showed a significant peak at a damaged location. Because the curvature of an elastic beam is inversely proportional to the flexural rigidity of the section, a loss of flexural rigidity will cause an increase of curvature. However, for the higher modes, there were also some small peaks observed at the undamaged locations. If the small peaks are observed in practical applications, the engineer may be misled regarding the damage locations. Wahab and Roeck [4] further proposed a curvature damage factor (CDF) that summarizes in one number the differences in curvature mode shapes for all modes for each measured point. They found that the spatial distribution of CDF can show a clear peak at the position of damage in a continuous beam. Chandrashekhar and Ganguli [5] proposed a fuzzy logic system for structural damage detection using modal curvatures. Their parametric studies

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“…Some are based on the use of frequency response functions (FRFs) as damage-sensitive parameter [17][18][19]; others as the frequency response curvature method and the gapped smoothing method proposed in References [20,21], both define the damage index in terms of the variation of curvature estimated from operational deformed shapes recovered from FRFs. Some are based on the use of frequency response functions (FRFs) as damage-sensitive parameter [17][18][19]; others as the frequency response curvature method and the gapped smoothing method proposed in References [20,21], both define the damage index in terms of the variation of curvature estimated from operational deformed shapes recovered from FRFs.…”

Section: Introductionmentioning

confidence: 99%

Seismic health monitoring of an instrumented multistory building using the interpolation method

Limongelli

2014

Earthq Engng Struct Dyn

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SUMMARY In this paper, a new approach to structural damage localization is presented using as damage feature the interpolation error related to the use of a spline function in modeling the operational deformed shapes of the structure. Statistically significant variations of the interpolation error between the undamaged and the inspection phase indicate the onset of damage. A threshold value of the damage feature is defined in terms of the tolerable probability of false alarm to select variations of the interpolation error because of damage from those due to random sources. The method is successfully applied to a calibrated model of the factor building a real densely instrumented building at the University of California, Los Angeles. Results show that the method is effective for damage localization for both single and multiple locations of damage also in case of responses corrupted by noise. Copyright © 2014 John Wiley & Sons, Ltd.

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A frequency response function change method for damage localization and quantification in a shear building under ground excitation

Cited by 10 publications

References 20 publications

Transfer function‐based Bayesian damage detection under seismic excitation

Transfer function‐based Bayesian damage detection under seismic excitation

Damage detection in shear buildings using different estimated curvature

Seismic health monitoring of an instrumented multistory building using the interpolation method

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