• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.2
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• pp.87-94
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• 2012

A damage estimation method of wind turbine tower using natural frequency and mode shape is presented for effective condition monitoring. Dynamic analysis for a wind turbine was carried out to obtain the response of tower from which modal properties were identified. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. The changes of modal property were calculated using a program for modal parameter estimation. Damage locations and severities could be successfully estimated for 10 damage cases including multi-damage cases using the trained neural network. The damage severities for very small damages generally tends to be slightly under-estimated however, the identified damage locations agreed reasonably well with the accurate locations. Enhancement of the estimation result for very small damage and verification of the proposed method through experiment will be carried out by further study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1577-1582
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• 2000

In this study, the experimental modal analysis is performed to investigate the dynamic characteristics of slider-air bearings in hard disk drives. Bump response of the slider is acquired by measuring the relative velocity for two points using the laser interferometer, in which the disk is scratched lightly by a sharp knife to make a bump. From the measurements, the modal parameters of the head slider, modal frequencies and damping ratios of roll and pitch, are estimated by data processing and parameter estimation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.124-127
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• 2005

As computer capability and test skill become more and more advanced, finite element method and modal test are being widely applied in engineering design. In order to correlate and reconcile the inevitable discrepancies between the analytical and experimental models, many techniques have been developed. Among these methods, multiple-system methods are known as the effective tools in that they can supply the rich modal data available which are experimentally obtained. These abundant modal data can help structural system parameters estimated well. Multiple-system methods can be classified into the structural modification methods and feedback controller methods. The structural modification methods need the physical attachment of structures and their concept may limit the application of them. To overcome this drawback, the feedback controller methods are addressed which enable us to get more modal data without the structural change. Mode decoupling controller(MDC), one of them, is to use acceleration out)ut feedback to perturb an open-loop system. The output feedback controller generally cannot guarantee the stability of a closed-loop system. However, MDC can solve this problem under the certain constraints. So far, MDC utilizes accelerations as the sensor signals. In this research, strain sensors are going to be picked up to apply to the MDC. Strain output is recently used for structural system identification due to the drastically improved and miniaturized strain sensor. In this paper, we show that the MDC using strain output has differences compared with acceleration output in estimating the structural system parameters. The associated simulation is performed to demonstrate the above mentioned characteristics.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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• pp.122-132
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• 2005

This paper presents a novel approach based on Prony method to analysis of small signal stability in power system. Prony method is a valuable tool in identifying transfer function and estimating the modal parameter of power system oscillation from measured or computed discrete time signal. This paper define the relative residue of time signal and propose the condition to select low frequency oscillation in each generator. This paper describes the application results of proposed algorithm with respect to KEPCO systems. Simulation results show that the proposed algorithm can be used as another tools of power systems analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.667-675
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• 2012

A damage estimation method for support structure of offshore wind turbine using modal parameters is presented for effective structural health monitoring. Natural frequencies and mode shapes for a support structure with monopile of an offshore wind turbine were calculated considering soil condition and added mass. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. Natural frequencies and mode shapes for 10 prospective damage cases were input to the trained neural network for damage estimation. The identified damage locations and severities agreed reasonably well with the accurate damages. Multi-damage cases could also be successfully estimated. Enhancement of estimation result using another parameters as input to neural network will be carried out by further study. Proposed method could be applied to other type of support structure of offshore wind turbine for structural health monitoring.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.175-182
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• 1994

As for the safety evaluation of existing large-scale structures, methods for estimation of the structural and dynamic properties are studied. Sequential prediction error method in time domain and improved FRF estimator in frequency domain are comparatively studied. For this purpose, impact tests of 2 bay 3 floor steel frame structure are performed. Results from both methods are found to be consistent to each others, however those from the finite-element analysis are slightly different from experimental results.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.349-375
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• 2016

The tension of an arch bridge hanger is estimated using a number of experimentally identified modal frequencies. The hanger is connected through metallic plates to the bridge deck and arch. Two different categories of model classes are considered to simulate the vibrations of the hanger: an analytical model based on the Euler-Bernoulli beam theory, and a high-fidelity finite element (FE) model. A Bayesian parameter estimation and model selection method is used to discriminate between models, select the best model, and estimate the hanger tension and its uncertainty. It is demonstrated that the end plate connections and boundary conditions of the hanger due to the flexibility of the deck/arch significantly affect the estimate of the axial load and its uncertainty. A fixed-end high fidelity FE model of the hanger underestimates the hanger tension by more than 20 compared to a baseline FE model with flexible supports. Simplified beam models can give fairly accurate results, close to the ones obtained from the high fidelity FE model with flexible support conditions, provided that the concept of equivalent length is introduced and/or end rotational springs are included to simulate the flexibility of the hanger ends. The effect of the number of experimentally identified modal frequencies on the estimates of the hanger tension and its uncertainty is investigated.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.3
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• pp.48-55
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• 1990

A new curve fitting algorithm based on modal analysis is introduced for extracting the modal parameters from the measured frequency responses. To compensate the effect of cut-off frequency ranges the transfer function including residual mass and residual flexibility is employed. Model parameters are computed from the newly defined form of transfer function in a simple way. The accuracy of this algorithm is proved by applying to the 3 degrees of freedom model and vibration of cantilever beam.

• 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.

• Smart Structures and Systems
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• v.15 no.3
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• pp.717-733
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• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.