• Smart Structures and Systems
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• v.9 no.5
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• pp.441-459
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• 2012

Identification of vibration parameters from the analysis of the dynamic response of a structure plays a key role in current health monitoring systems. This study evaluates the capabilities of the recently developed Synchrosqueezed Wavelet Transform (SWT) to extract instant frequencies and damping values from the simulated noise-contaminated response of a structure. Two approaches to estimate the modal damping ratio from the results of the SWT are presented. The results obtained are compared to other signal processing methods based on Continuous Wavelet (CWT) and Hilbert-Huang (HHT) transforms. It was found that the time-frequency representation obtained via SWT is sharped than the obtained using just the CWT and it allows a more robust extraction of the individual modal responses than using the HHT. However, the identification of damping ratios is more stable when the CWT coefficients are employed.

• Smart Structures and Systems
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• v.33 no.2
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• pp.145-163
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• 2024

The evaluation of dynamic characteristics of bridges under operational traffic loads is a crucial aspect of bridge structural health monitoring. In the vehicle-bridge interaction (VBI) system, the vibration responses of bridge exhibit time-varying characteristics. To address this issue, an accurate time-frequency analysis method that combines the autoregressive power spectrum based empirical wavelet transform (AR-EWT) and local maximum synchrosqueezing transform (LMSST) is proposed to identify the time-varying instantaneous frequencies (IFs) of the bridge in the VBI system. The AR-EWT method decomposes the vibration response of the bridge into mono-component signals. Then, LMSST is employed to identify the IFs of each mono-component signal. The AR-EWT combined with the LMSST method (AR-EWT+LMSST) can resolve the problem that LMSST cannot effectively identify the multi-component signals with weak amplitude components. The proposed AR-EWT+LMSST method is compared with some advanced time-frequency analysis techniques such as synchrosqueezing transform (SST), synchroextracting transform (SET), and LMSST. The results demonstrate that the proposed AR-EWT+LMSST method can improve the accuracy of identified IFs. The effectiveness and applicability of the proposed method are validated through a multi-component signal, a VBI numerical model with a four-degree-of-freedom half-car, and a VBI model experiment. The effect of vehicle characteristics, vehicle speed, and road surface roughness on the identified IFs of bridge are investigated.

• Earthquakes and Structures
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• v.15 no.3
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• pp.263-273
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• 2018

Operational modal analysis is being widely used in aerospace, mechanical and civil engineering. Common research fields include optimal design and rehabilitation under dynamic loads, structural health monitoring, modification and control of dynamic response and analytical model updating. In many practical cases, influence of noise contamination in the recorded data makes it difficult to identify the modal parameters accurately. In this paper, an improved frequency domain method called Enhanced Least Square Complex Frequency (eLSCF) is developed to extract modal parameters from noisy recorded data. The proposed method makes the use of pre-defined approximate mode shape vectors to refine the cross-power spectral density matrix and extract fundamental frequency for the mode of interest. The efficiency of the proposed method is illustrated using an example five story shear frame loaded by random excitation and different noise signals.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.143-150
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• 2005

To verify applicability of multi-dimensional spectral analysis (MDSA) fur noise source identification two different approaches which are frequency response and coherent function have been investigated. The coherence function approach appears able to separate the correlated system when the noise sources were coherent. In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using MDSA method. Firstly, to identify the applicability of MDSA method, 4-inputs of vehicle HVAC system were the signals measured by accelerometers attached on the selected noise sources which were composed of blower, evaporator, heater and duct. While 1-output which was driver's position sound was the SPL signals measured by a remote microphone, when the blower motor was operating. We identify efficiency of systems modeled with four Inputs/single output through ordinary coherence function (OCF) and partial coherence function (PCF). As a result of experiment, the blower accounted for $62-88\%$ of the overall level of sound energy density. Also, according to the analysis of acoustic signal and vibration signals measurement, an investigation of the noise source identification in the vehicle HVAC is presented. With the sound intensity method, the major sources of the vehicle HVAC radiation are verified. Also the method of improving the noise reduction is proposed by attaching damping patch access to blower motor and noise reduction is verified.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.327-344
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• 2013

Beam string structure (BSS) is introduced as a new type of hybrid prestressed string structures. The composition and mechanics features of BSS are discussed. The main principles of wavelet packet transform (WPT), principal component analysis (PCA) and support vector machine (SVM) have been reviewed. WPT is applied to the structural response signals, and feature vectors are obtained by feature extraction and PCA. The feature vectors are used for training and classification as the inputs of the support vector machine. The method is used to a single one-way arched beam string structure for damage detection. The cable prestress loss and web members damage experiment for a beam string structure is carried through. Different prestressing forces are applied on the cable to simulate cable prestress loss, the prestressing forces are calculated by the frequencies which are solved by Fourier transform or wavelet transform under impulse excitation. Test results verify this method is accurate and convenient. The damage cases of web members on the beam are tested to validate the efficiency of the method presented in this study. Wavelet packet decomposition is applied to the structural response signals under ambient vibration, feature vectors are obtained by feature extraction method. The feature vectors are used for training and classification as the inputs of the support vector machine. The structural damage position and degree can be identified and classified, and the test result is highly accurate especially combined with principle component analysis.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.414-419
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• 2007

The contact characteristics of the current collection system are investigated by analyzing data collected during a test run of the Korean high speed rail vehicle. For the analysis, the signals from accelerometers and load cells attached to the various parts of the pantograph are analyzed in both the time and frequency domains. In the frequency domain, the pantograph response consists of low frequency components related to the rigid-body motion of the panhead assembly and high frequency components due to the structural vibration modes of the pantograph. The analysis shows that the inclusion of the high frequency structural vibration modes of the pantograph in the contact force calculation has a negligible effect on the predicted mean value of the contact force but significantly affects the magnitude of its fluctuations. This finding implies that numerical simulations using lumped element models of the pantograph may accurately predict the mean contact force but is limited in its capacity for predicting the fluctuation about the mean. Since the ratio of the fluctuation to the mean in the contact force increases with increased train speed, the limitation of the predictions based on numerical simulation results becomes more pronounced at higher train speed.

• Journal of KSNVE
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• v.8 no.6
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• pp.1103-1112
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• 1998

A new time series method, directional ARMAX (dARMAX) model-based approach. is proposed for rotor dynamics identification. The dARMAX processes complex-valued signals, utilizing the complex modal testing theory which enables the separation of the backward and forward modes in the two-sided frequency domain and makes effective modal parameter identification possible, to account for the dynamic characteristics inherent in rotating machinery. This paper is divided into two parts : The dARMAX modeling, analysis. and fitting strategy are presented in the first part. whereas a evaluation of its performance characteristics based on both simulated and experimental data is presented in the second.

• Smart Structures and Systems
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• v.10 no.2
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• pp.131-154
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• 2012

In this paper, it is aimed to determine the seismic behaviour of highway bridges by nondestructive testing using ambient vibration measurements. Eynel Highway Bridge which has arch type structural system with a total length of 216 m and located in the Ayvaclk county of Samsun, Turkey is selected as an application. The bridge connects the villages which are separated with Suat U$\breve{g}$urlu Dam Lake. A three dimensional finite element model is first established for a highway bridge using project drawings and an analytical modal analysis is then performed to generate natural frequencies and mode shapes in the three orthogonal directions. The ambient vibration measurements are carried out on the bridge deck under natural excitation such as traffic, human walking and wind loads using Operational Modal Analysis. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, two output-only system identification techniques are employed namely, Enhanced Frequency Domain Decomposition technique in the frequency domain and Stochastic Subspace Identification technique in time domain. Analytical and experimental dynamic characteristic are compared with each other and finite element model of the bridge is updated by changing of boundary conditions to reduce the differences between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of highway bridges. After finite element model updating, maximum differences between the natural frequencies are reduced averagely from 23% to 3%. The updated finite element model reflects the dynamic characteristics of the bridge better, and it can be used to predict the dynamic response under complex external forces. It is also helpful for further damage identification and health condition monitoring. Analytical model of the bridge before and after model updating is analyzed using 1992 Erzincan earthquake record to determine the seismic behaviour. It can be seen from the analysis results that displacements increase by the height of bridge columns and along to middle point of the deck and main arches. Bending moments have an increasing trend along to first and last 50 m and have a decreasing trend long to the middle of the main arches.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.12
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• pp.1120-1131
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• 2011

Researches using time reversal acoustics(TRA) for impact localization have been paid attention to recently. Dispersion characteristics of Lamb waves, which restrict the utility of classical nondestructive evaluation based on time-of-flight information, can be compensated through the application of TRA to Lamb waves on a plate. This study investigates the spatial focusing performance of time reversal Lamb waves on a plate using finite element analysis. In particular, the virtual sensor effect caused by multiple wave reflections at the boundaries of a plate is shown to enable the spatial focusing of Lamb waves though a very small number of surface-bonded piezoelectric(PZT) sensors are available. The time window size of forward response signals, are normalized with respect to the number of virtual active sensors. Then their effects on the spatial focusing performance of Lamb waves are investigated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.418-429
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• 2011

Researches using time reversal acoustics (TRA) for impact localization have been paid attention to recently. Dispersion characteristics of Lamb waves, which restrict the utility of classical nondestructive evaluation based on time-of-flight information, can be compensated through the application of TRA to Lamb waves on a plate. This study investigates the spatial focusing performance of time reversal Lamb waves on a plate using finite element analysis. In particular, the virtual sensor effect caused by multiple wave reflections at the boundaries of the plate is shown to enable the spatial focusing of Lamb waves though a very small number of surface-bonded piezoelectric (PZT) sensors are available. The time window size of forward response signals, are normalized with respect to the number of virtual active sensors. Then their effects on the spatial focusing performance of Lamb waves are investigated.