• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.3
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• pp.101-107
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• 2014

Damage location and extent of structure could be detected by the inverse analysis on dynamic response properties such as frequencies and mode shapes. The dynamic response of building structures has many noise and affected by nonstructural members and, above all, the behavior of building structure is more complex than civil structure and this makes the damage detection difficult. In recent researches the damage is detected by the indirect index such as sensitivity or assumed values. However, for the more reasonable damage detection, it needs to use the damage index directly induced from dynamic equation. The purpose of this study is to provide the damage detection method on shear building structures by the damage index directly induced from dynamic equation. The provided damage index could be estimated from measured mode shape of undamaged structure and frequency difference between undamaged and damaged structure. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. The damage index at damaged story represents (-) sign and 15 times than other undamaged sories.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.441-463
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• 2013

In this paper, a simplified planar model is developed for damage estimation of interlocked caisson systems. Firstly, a conceptual dynamic model of the interlocked caisson system is designed on the basis of the characteristics of existing harbor caisson structures. A mass-spring-dashpot model allowing only the sway motion is formulated. To represent the condition of interlocking mechanisms, each caisson unit is connected to adjacent ones via springs and dashpots. Secondly, the accuracy of the planar model's vibration analysis is numerically evaluated on a 3-D FE model of the interlocked caisson system. Finally, the simplified planar model is employed for damage estimation in the interlocked caisson system. For localizing damaged caissons, a damage detection method based on modal strain energy is formulated for the caisson system.

• Earthquakes and Structures
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• v.22 no.1
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• pp.1-13
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• 2022

When a building suffers damages under moderate to severe loading condition, its physical properties such as damping and stiffness parameters will change. There are different practical methods besides various numerical procedures that have successfully detected a range of these changes. Almost all the previous proposed methods used to work with translational components of mode shapes, probably because extracting these components is more common in vibrational tests. This study set out to investigate the influence of using both rotational and translational components of mode shapes, in detecting damages in 3-D steel structures elements. Three different sets of measured components of mode shapes are examined: translational, rotational, and also rotational/translational components in all joints. In order to validate our assumptions two different steel frames with three damage scenarios are considered. An iterative model updating program is developed in the MATLAB software that uses the OpenSees as its finite element analysis engine. Extensive analysis shows that employing rotational components results in more precise prediction of damage location and its intensity. Since measuring rotational components of mode shapes still is not very convenient, modal dynamic expansion technique is applied to generate rotational components from measured translational ones. The findings indicated that the developed model updating program is really efficient in damage detection even with generated data and considering noise effects. Moreover, methods which use rotational components of mode shapes can predict damage's location and its intensity more precisely than the ones which only work with translational data.

• Smart Structures and Systems
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• v.14 no.4
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• pp.569-594
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• 2014

Damage detection methods based on modal analysis have been widely studied in recent years. However the calculation of mode shapes in real structures can be time consuming and often requires dedicated software programmes. In the present paper the combined application of proper orthogonal decomposition and gapped smoothing method to structural damage detection is presented. The first is used to calculate the dynamic shapes of a damaged structural element using only the time response of the system while the second is used to derive a reference baseline to which compare the data coming from the damaged structure. Experimental verification is provided for a beam case while numerical analyses are conducted on plates. The introduction of a stiffener on a plate is investigated and a method to distinguish its influence from that of a defect is presented. Results highlight that the derivatives of the proper orthogonal modes are more effective damage indices than the modes themselves and that they can be used in damage detection when only data from the damaged structure are available. Furthermore the stiffened plate case shows how the simple use of the curvature is not sufficient when analysing complex components. The combined application of the two techniques provides a possible improvement in damage detection of typical aeronautical structures.

• Journal of Korean Society of Steel Construction
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• v.15 no.1
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• pp.41-50
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• 2003

Nondestructive Damage Evaluation (NDE) techniques yield the damage location and its size from the modal characteristics of pre-damaged and post-damaged structures. To predict the system reliability of the aging structure, results from the NDE are integrated into the element/component failure probabilities. The element/component failure probabilities can be calculated from failure functions for each element/component with the aid of techniques from a structural reliability analysis. In this paper, a method to estimate the system reliability of a structure that is based on the reliabilities of elements/components in a given structure is presented. The efficacy of the combination of the nondestructive damage detection and the structural reliability evaluation is demonstrated using pre-damaged and post-damaged modal data obtained from numerical simulations of a rigid frame.

• Journal of Navigation and Port Research
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• v.32 no.3
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• pp.215-221
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• 2008

Dynamic characteristics of a structure, i.e., natural frequency and mode shape, have been widely using as an input data in the area of structural integrity or health monitoring which combined with the damage evaluation and structural system identification techniques. It is very difficult, however, to get those information by the conventional modal analysis method from large structures, such as the offshore structure or the long-span bridge, since the source of vibration is not available. In this paper, a method to obtain the frequencies and the mode shapes of a large span truss structure using only acceleration responses is studied. The calculation procedures to obtain acceleration responses and frequency response functions are provided utilizing a numerical model of the truss, and the process to extract natural frequencies and mode shapes from the modal analysis is cleary explained. The extracted mode shapes by proposed method are compared with those from eigenvalue analysis for the estimation of accuracy. The validity of the mode shapes is also demonstrated using an existing damage detection technique for the truss structure by simulated damage cases.

• Structural Engineering and Mechanics
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• v.46 no.5
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• pp.615-627
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• 2013

One of the most common defects in reinforced concrete bridge decks is corrosion of steel reinforcing bars. This invisible defect reduces the deck stiffness and affects the bridge's serviceability. Regular monitoring of the bridge is required to detect and control this type of damage and in turn, minimize repair costs. Because the corrosion is hidden within the deck, this type of damage cannot be easily detected by visual inspection and therefore, an alternative damage detection technique is required. This research develops a non-destructive method for detecting reinforcing bar corrosion. Experimental modal analysis, as a non-destructive testing technique, and finite element (FE) model updating are used in this method. The location and size of corrosion in the reinforcing bars is predicted by creating a finite element model of bridge deck and updating the model characteristics to match the experimental results. The practicality and applicability of the proposed method were evaluated by applying the new technique to a two spans bridge for monitoring steel bar corrosion. It was shown that the proposed method can predict the location and size of reinforcing bars corrosion with reasonable accuracy.

• Journal of Wind Energy
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• v.9 no.4
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• pp.16-23
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• 2018

A damage detection method for the tripod support structure of offshore wind turbines is presented for structural health monitoring. A finite element model of a prototype tripod support structure is established and the modal properties are calculated. The degree and location of the damage are estimated based on the neural network technique using the changes of natural frequencies and mode shape due to the damage. The stress distribution occurring in the support structure is obtained by a dynamic analysis for the wind turbine system to select the output data of the neural network. The natural frequencies and mode shapes for 36 possible damage scenarios were used for the input data of the learned neural network for damage assessment. The estimated damages agreed reasonably well with the accurate ones. The presented method could be effectively applied for damage detection and structural health monitoring of various types of support structures of offshore wind turbines.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.395-406
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• 2016

Modal parameter identification has received much attention recently for their usefulness in earthquake engineering, damage detection and structural health monitoring. The identification method based on Matrix Pencil technique is adopted in this paper to identify structural modal parameters, such as natural frequencies, damping ratios and modal shapes using impulse vibration responses. This method can also be applied to dynamic responses induced by stationary and white-noise inputs since the auto- and cross-correlation function of the two outputs has the same form as the impulse response dynamic functions. Matrix Pencil method is very robust to noise contained in the measurement data. It has a lower variance of estimates of the parameters of interest than the Polynomial Method, and is also computationally more efficient. The numerical simulation results show that this technique can identify modal parameters accurately even if the noise level is high.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.107-127
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• 2022

Structural health monitoring (SHM) has been related to damage identification with either operational loads or other environmental loading playing a significant complimentary role in terms of structural safety. In this study, a non-parametric method of time frequency analysis on the measurement is used to address the time-frequency representation for modal parameter estimation and system damage identification of structure. The method employs the wavelet decomposition of dynamic data by using the modified complex Morlet wavelet with variable central frequency (MCMW+VCF). Through detail discussion on the selection of model parameter in wavelet analysis, the method is applied to study the dynamic response of both steel structure and reinforced concrete frame under white noise excitation as well as earthquake excitation from shaking table test. Application of the method to building earthquake response measurement is also examined. It is shown that by using the spectrogram generated from MCMW+VCF method, with suitable selected model parameter, one can clearly identify the time-varying modal frequency of the reinforced concrete structure under earthquake excitation. Discussions on the advantages and disadvantages of the method through field experiments are also presented.