• Structural Engineering and Mechanics
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• v.56 no.2
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• pp.293-315
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• 2015

While most of researches on system identification of building structures are aimed at finding modal parameters first and identifying the corresponding physical parameters by using the transformation in terms of transfer functions and cross spectra, etc., direct physical parameter system identification methods have been proposed recently. Due to the problem of signal/noise (SN) ratios, the previous methods are restricted mostly to earthquake records or forced vibration data. In this paper, a theoretical investigation is performed on the influence of wind disturbances on stiffness identification of building structures using micro-tremor at limited floors. It is concluded that the influence of wind disturbances on stiffness identification of building structures using micro-tremor at limited floors is restricted in case of using time-series data for low-rise buildings and does not cause serious problems.

• Wind and Structures
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• v.17 no.6
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• pp.609-627
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• 2013

The Yingxian wooden tower in China is currently the tallest wooden tower in the world. It was built in 1056 AD and is 65.86 m high. Field measurements of wind speed and wind-induced response of this tower are conducted. The wind characteristics, including the average wind speed, wind direction, turbulence intensity, gust factor, turbulence integral length scale and velocity spectrum are investigated. The power spectral density and the root-mean-square wind-induced acceleration are analyzed. The structural modal parameters of this tower are identified with two different methods, including the Empirical Mode Decomposition (EMD) combined with the Random Decrement Technique (RDT) and Hilbert transform technique, and the stochastic subspace identification (SSI) method. Results show that strong wind is coming predominantly from the West-South of the tower which is in the same direction as the inclination of the structure. The Von Karman spectrum can describe the spectrum of wind speed well. Wind-induced torsional vibration obviously occurs in this tower. The natural frequencies identified by EMD, RDT and Hilbert Transform are close to those identified by SSI method, but there is obvious difference between the identified damping ratios for the first two modes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.287-292
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• 2005

This paper presents a rational polynomial approximation method to estimate modal parameters of wind excited structures using incomplete noisy measurements of structural responses and partial measurements of wind velocities only. A stochastic model of the excitation wind force acting on the structure is estimated from partial measurements of wind velocities. Then the transfer functions of the structure are approximated as rational polynomial functions. From the poles and zeros of the estimated rational polynomial functions, the modal parameters, such as natural frequencies, damping ratios, and mode shapes are extracted. Since the frequency characteristics of wind forces acting on structures can be assumed as a smooth Gaussian process especially around the natural frequencies of the structures according to the central limit theorem (Brillinger, 1969; Yaglom, 1987), the estimated modal parameters are robust and reliable with respect to the assumed stochastic input models. To verify the proposed method, the modal parameters of a TV transmission tower excited by gust wind are estimated. Comparison study with the results of other researchers shows the efficacy of the suggested method.

• Steel and Composite Structures
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• v.7 no.6
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• pp.487-502
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• 2007

In recent decades there has been a trend towards improved mechanical characteristics of materials used in footbridge construction. It has enabled engineers to design lighter, slender and more aesthetic structures. As a result of these construction trends, many footbridges have become more susceptible to vibrations when subjected to dynamic loads. In addition to this, some inherit modelling uncertainties related to a lack of information on the as-built structure, such as boundary conditions, material properties, and the effects of non-structural elements make difficult to evaluate modal properties of footbridges, analytically. For these purposes, modal testing of footbridges is used to rectify these problems after construction. This paper describes an arch type steel footbridge, its analytical modelling, modal testing and finite element model calibration. A modern steel footbridge which has arch type structural system and located on the Karadeniz coast road in Trabzon, Turkey is selected as an application. An analytical modal analysis is performed on the developed 3D finite element model of footbridge to provide the analytical frequencies and mode shapes. The field ambient vibration tests on the footbridge deck under natural excitation such as human walking and traffic loads are conducted. The output-only modal parameter identification is carried out by using the peak picking of the average normalized power spectral densities in the frequency domain and stochastic subspace identification in the time domain, and dynamic characteristics such as natural frequencies mode shapes and damping ratios are determined. The finite element model of footbridge is calibrated to minimize the differences between analytically and experimentally estimated modal properties by changing some uncertain modelling parameters such as material properties. At the end of the study, maximum differences in the natural frequencies are reduced from 22% to only %5 and good agreement is found between analytical and experimental dynamic characteristics such as natural frequencies, mode shapes by model calibration.

• Smart Structures and Systems
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• v.15 no.1
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• pp.227-244
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• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.149-160
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• 2008

In this study, the research was carried out on how to identify the modal parameter by acquiring the output response of the structure only through the smart sensor system. The objective of this research is to verify the performance and the on-site adaptability of the smart sensor system that have been actively researched as the advanced measuring system so far. Smart Sensor System was developed so that the real-time dynamic measurement can be performed by means of MEMS-type accelerated sensor, 8 bit CPU, wireless MODEM. In the modal parameter identification test, random excitation was added to the cantilever beam, and then the response of the structure was obtained using the smart sensor system and the wire measurement system respectively. In analyzing the data, modal parameter was identified using NExT & ERA algorithm. Furthermore, the optimal measurement location was selected through EOT algorithm in order to obtain the qualified output response. Result of the test, it was possible to verify the on-site applicability of the smart sensor.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.863-868
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• 2002

Operational Modal Analysis also known as Ambient Modal Analysis has an increasing interest in mechanical engineering. Especially on big structures where the excitation and not less important the determination of the forces is most often a problem. In a structure like a wind turbine wing where the modes occur both close in frequency and hi-directional the ambient excitation has big advantages. In this paper modal parameters are identified from the wing by operational modal analysis. For the parameter identification both parametric and non-parametric techniques are used. Advantages and disadvantages are discussed and results from the different techniques are compared

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.363-368
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• 1993

Hilbert Transform has been used for detection of nonlinearity in modal analysis. HTD(Hilbert Transform Describers) are used to quantify and identify nonlinearity. Mottershead and Stanway method for identification of N-th power velocity nonlinear damping are extended to P-th power displacement stiffness, N-th power velocity damping and dry friction. Time domain and frequency domain data are used and HTD and Mottershead methods are combined for identification of nonlinear parameters in this paper. Computer simulations and experimental results are shown to verify nonlinear structure identification methods.

• Journal of Ocean Engineering and Technology
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• v.10 no.4
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• pp.17-27
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• 1996

본 연구는 진동반응측정을 통해 구조물의 손상을 비파괴적으로 예측하는 분야에 속한다. 건물, 교량, 댐, 해양자켓, 원자력 발전소 등의 구조물에서 시기적절하고 정확한 손상의 발견은 치명적인 구조적 결함의 예방을 위해 필수적이다. 구조물의 진동반응을 측정하여 구조물의 손상발견을 예측하려는 연구는 지난 80년대 이후 활발히 수행되어 오고 있으며, 본연구는 구조물 고유진동수의 변화로 부터 구조물 강성도의 변화를 모니터링하는 연구분야에 속한다. 본 연구의 목적은 현존하는 시스템동일화 (system identification)에 의한 손상발견법의 적합성을 검증하는 것이다. 먼저, 실물실험된 삼차원 트러스교량이 선택되었다. 다음으로, 시스템 동일화 개념에 기초한 손상발견법이 요약되었다. 마지막으로, 시스템 동일화 손상발견법을 실물트러스에 적용하여 적합성을 실험하였다.