• Smart Structures and Systems
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• v.14 no.4
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• pp.595-615
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• 2014

This study aims to investigate the relationship between structural damage and sensitivity indices using the Hilbert-Huang transform (HHT) method. Two damage detection indices are proposed: the ratio of bandwidth (RB), and the ratio of effective stiffness (RES). The nonlinear four bays multiple degree of freedom models with various predominant frequencies are constructed using the SAP2000 program. Adjusted PGA earthquake data (Japan 311, Chi-Chi 921) are used as the excitations. Next the damage detection indices obtained using the HHT and the fast Fourier transform (FFT) methods are evaluated based on the acceleration responses of the structures to earthquakes. Simulation results indicate that, the column of the 1 st floor is the first yielding position and the RB value is changed when the RES<90% in all cases. Moreover, the RB value of the 1 st floor changes more sensitive than those from the top floor. In addition, when the structural response is nonlinear (i.e., RES<100%), the RB and the RES curves indicate the incremental change in the HHT spectra. However, the same phenomenon can be found from FFT spectra only when the stiffness reduction is large enough. Therefore, the RB estimated from the smoothed HHT spectra is an effective and sensitive index for detecting structural damage.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.813-831
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• 2011

This paper presents an efficient version of Hilbert-Huang transform for nonlinear non-stationary systems analyses. An ensemble empirical mode decomposition (EEMD) is introduced to alleviate the problem of mode mixing between intrinsic mode functions (IMFs) decomposed by EMD. Yet the problem has not been fully resolved when a signal of a similar scale resides in different IMF components. Instead of using a trial and error method to select the "best" outcome generated by EEMD, a hybrid algorithm based on EEMD and EMD is proposed for multi-mode signal processing. The developed approach comprises the steps from a bandpass filter design for regrouping modes of the IMFs obtained from EEMD, to the mode extraction using EMD, and to the assessment of each mode in the marginal spectrum. A simulated two-mode signal is tested to demonstrate the efficiency and robustness of the approach, showing average relative errors all equal to 1.46% for various noise levels added to the signal. The developed approach is also applied to a real bridge structure, showing more reliable results than the pure EMD. Discussions on the mode determination are offered to explain the connection between modegrouping form on the one hand, and mode-grouping performance on the other.

• Smart Structures and Systems
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• v.19 no.6
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• pp.653-663
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• 2017

The modal parameters of the deck of Runyang Suspension Bridge (RSB) as well as their relationships with wind and temperature are studied based on the data recorded by its Structural Health Monitoring System (SHMS). Firstly, frequency analysis on the vertical responses at the two sides of the deck is carried out to distinguish the vertical and torsional vibration modes. Then, the vertical, torsional and lateral modal parameters of the deck of RSB are identified using Hilbert-Huang Transform (HHT) and validated by the identified results before RSB was opened to traffic. On the basis of this, the modal frequencies and damping ratios of RSB during the whole process of Typhoon Masta are obtained. And the correlation analysis on the modal parameters and wind environmental factors is then conducted. Results show that the HHT can achieve an accurate modal identification of RSB and the damping ratios show an obvious decay trend as the frequencies increase. Besides, compared to frequencies, the damping ratios are more sensitive to the environmental factors, in particular, the wind speed. Further study on configuring the variation law of modal parameters related with environmental factors should be continued.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.58-67
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• 2016

With the large amount of complex network data that is increasingly available on the Web, link prediction has become a popular data-mining research field. The focus of this paper is on a link-prediction task that can be formulated as a binary classification problem in complex networks. To solve this link-prediction problem, a sparse-classification algorithm called "Truncated Kernel Projection Machine" that is based on empirical-feature selection is proposed. The proposed algorithm is a novel way to achieve a realization of sparse empirical-feature-based learning that is different from those of the regularized kernel-projection machines. The algorithm is more appealing than those of the previous outstanding learning machines since it can be computed efficiently, and it is also implemented easily and stably during the link-prediction task. The algorithm is applied here for link-prediction tasks in different complex networks, and an investigation of several classification algorithms was performed for comparison. The experimental results show that the proposed algorithm outperformed the compared algorithms in several key indices with a smaller number of test errors and greater stability.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.192-198
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• 2005

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The results by EMD method whichhas used only output vibration data are almost identical to the results by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.699-704
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• 2004

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The result by EMD method which has used only output vibration data is almost identical to the result by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• Structural Engineering and Mechanics
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• v.70 no.5
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• pp.623-637
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• 2019

This paper analyzes the non-stationary vibration and super-harmonic resonances in nonlinear dynamic motion of viscoelastic nano-resonators. For this purpose, a new coupled size-dependent model is developed for a plate-shape nano-resonator made of nonlinear viscoelastic material based on modified coupled stress theory. The virtual work induced by viscous forces obtained in the framework of the Leaderman integral for the size-independent and size-dependent stress tensors. With incorporating the size-dependent potential energy, kinetic energy, and an external excitation force work based on Hamilton's principle, the viscous work equation is balanced. The resulting size-dependent viscoelastically coupled equations are solved using the expansion theory, Galerkin method and the fourth-order Runge-Kutta technique. The Hilbert-Huang transform is performed to examine the effects of the viscoelastic parameter and initial excitation values on the nanosystem free vibration. Furthermore, the secondary resonance due to the super-harmonic motions are examined in the form of frequency response, force response, Poincare map, phase portrait and fast Fourier transforms. The results show that the vibration of viscoelastic nanosystem is non-stationary at higher excitation values unlike the elastic ones. In addition, ignoring the small-size effects shifts the secondary resonance, significantly.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.9
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• pp.1100-1106
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• 2012

This paper has presented the analysis of the micro-Doppler signatures scattered from the blades of the rotating propeller using the modified HHT method, one of the joint time-frequency analysis methods. The field scattered from the blade edge of the propeller was calculated using equivalent current method(ECM). After the acquisition of the scattered field data in the time domain, the modified HHT method was applied to analyze the micro-Doppler signature. The analysis results showed not only a good agreement with the realistic dynamic characteristic of the blade but also sinusoidally varing characteristics of the micro-Doppler signatures generated from rotating objects. It could be concluded that the joint time-frequency analysis via the modified HHT provided the discriminative characteristics for recognizing a small aircraft target with small RCS value.

• Smart Structures and Systems
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• v.25 no.1
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• pp.65-80
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• 2020

In order to protect a structure over its full life cycle, a novel tuned mass damper (TMD), the so-called semi-active eddy current pendulum tuned mass damper (SAEC-PTMD), which can retune its frequency and damping ratio in real-time, is proposed in this study. The structural instantaneous frequency is identified through a Hilbert-Huang transformation (HHT), and the SAEC-PTMD pendulum is adjusted through an HHT-based control algorithm. The eddy current damping parameters are discussed, and the relationship between effective damping coefficients and air gaps is fitted through a polynomial function. The semi-active eddy current damping can be adjusted in real-time by adjusting the air gap based on the linear-quadratic-Gaussian (LQG)-based control algorithm. To verify the vibration control effect of the SAEC-PTMD, an idealized linear primary structure equipped with an SAEC-PTMD excited by harmonic excitations and near-fault pulse-like earthquake excitations is proposed as one of the two case studies. Under strong earthquakes, structures may go into the nonlinear state, while the Bouc-Wen model has a wild application in simulating the hysteretic characteristic. Therefore, in the other case study, a nonlinear primary structure based on the Bouc-Wen model is proposed. An optimal passive TMD is used for comparison and the detuning effect, which results from the cumulative damage to primary structures, is considered. The maximum and root-mean-square (RMS) values of structural acceleration and displacement time history response, structural acceleration, and displacement response spectra are used as evaluation indices. Power analyses for one earthquake excitation are presented as an example to further study the energy dissipation effect of an SAECPTMD. The results indicate that an SAEC-PTMD performs better than an optimized passive TMD, both before and after damage occurs to the primary structure.

• Journal of Power Electronics
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• v.11 no.5
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• pp.759-766
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• 2011

This paper focuses on monitoring and predicting the short circuit faults of the rotor windings of large turbo-generator systems. For the purpose of increasing efficiency and decreasing maintenance cost, a method that combines the HHT (Hilbert Huang Transform) with a wavelet has been studied. This method is based on analyzing a classical Albright detecting coil. Due to the Empirical Mode Decomposition (EMD) and the Intrinsic Mode Functions (IMF) of the HHT the exact location of a short circuit of rotor windings may be given. However, a part of the useful information is eliminated by the unreasonable decomposing scale of the wavelet. Based on the thermodynamics modeling method, this study was illustrated with a 50MW turbo-generator system that is installed in Northern China. The analysis results, which have very good agreement with those of a previous study, show that the method of combining the HHT with a wavelet is an effective way to analyze and predict the short circuit faults of the rotor windings of large generators, such as supercritical turbo-generator systems and wind turbo-generator systems. This work can offer a useful reference for analyzing smart grids by improving the power quality of a distribution network that is supplied by a turbo-generator system.