• Journal of Advanced Marine Engineering and Technology
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• v.36 no.2
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• pp.258-266
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• 2012

Recently, Acoustic Emission (AE) technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the rolling element bearing problems and Wavelet transform is a powerful method to detect faults occurred on gearboxes. However, exact method for AE signal is not developed yet. Therefore, in this paper, two methods, which is Hilbert transforms (HT) and Hilbert-Huang transforms (HHT), will be compared for development a signal processing method for early fault detection system by using AE. AE signals were measured through a fatigue test. HHT has better advantages than HT because HHT can show the time-frequency domain result. But, HHT needs long time to process a signal, which has a lot of data, and has a disadvantage in de-noising filter.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.555-561
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• 2012

The Hilbert Huang Transform (HHT) technigue with Empirical Mode Decomposition (EMD) is one of the time-frequency domain analysis methods and it has several advantages such that analyzing non-stationary and nonlinear signal is possible. However, there are shortcomings in detecting near-range of frequencies and added noise signals. In this paper, to analyze characteristics of each method, HHT and Short-Time Fourier Transform (STFT) effective in dealing with stationary signals are compared. And with thermoacoustic instabilities signals from a Rijke tube test, HHT and the improved HHT with Ensemble Empirical Mode Decomposition (EEMD) are compared. The results show that the improved HHT is more appropriate than the original HHT due to the relative insensitivity to noise. Therefore it will result in more accurate analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1442-1448
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• 2009

Transient characteristics of a signal can be effectively exhibited in time-frequency domain. Hilbert-Huang Transform (HHT) is one of the time-frequency domain analysis methods. HHT is known for its several advantages over other signal analysis methods. The capability of analyzing non-stationary or nonlinear characteristics of a signal is the primary advantage of HHT. Moreover, it is known that HHT can provide fine resolution in high frequency region and handle large size data efficiently. In this study, the effectiveness of Hilbert-Huang transform is illustrated by employing structural systems undergoing impact. A simple discrete system and an axially oscillating cantilever beam undertaking periodic impulsive force are chosen to show the effectiveness of HHT.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.453-458
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• 2002

A recently developed Hilbert-Huang transform (HHT) technique is applied to the detection of the damage locations of bridge structures. The HHT may be used to identify the locations of damages which exhibit nonlinear and non-stationary behavior, since the instantaneous frequency characteristics of the measured signal can be analyzed by the HHT. Numerical simulations were conducted on two bridge systems with damages using controlled excitations with sweeping frequency. Nonlinear plastic model using a gap element is employed to model the behavior of the cracked elements in the numerical simulations. The results indicate that the HHT method can reasonably identify the damage locations based on a limited number of acceleration sensors. Experimental study has been 실so carried out on a steel frame to confirm the applicability of the HHT to detect a structural connection with loosened bolts.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.499-513
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• 2009

An economic signal in the real world usually reflects complex phenomena. One may have difficulty both extracting and interpreting information embedded in such a signal. A natural way to reduce complexity is to decompose the original signal into several simple components, and then analyze each component. Spectral analysis (Priestley, 1981) provides a tool to analyze such signals under the assumption that the time series is stationary. However when the signal is subject to non-stationary and nonlinear characteristics such as amplitude and frequency modulation along time scale, spectral analysis is not suitable. Huang et al. (1998b, 1999) proposed a data-adaptive decomposition method called empirical mode decomposition and then applied Hilbert spectral analysis to decomposed signals called intrinsic mode function. Huang et al. (1998b, 1999) named this two step procedure the Hilbert-Huang transform(HHT). Because of its robustness in the presence of nonlinearity and non-stationarity, HHT has been used in various fields. In this paper, we discuss the applications of the HHT and demonstrate its promising potential for non-stationary financial time series data provided through a Korean stock price index.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.159-168
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• 2002

A recently developed filbert-Huang transform (HHT) technique is applied to detect damage locations of bridge structures. The HHT may be used to identify the locations of damages which exhibit nonlinear and nonstationary behavior, since the HHT can show the instantaneous frequency characteristics of the signal. A series of numerical simulations were conducted for bridge pier systems with damages under a controlled load with sweeping frequency. The results of the numerical simulation study indicate that the HHT method can reasonably identify damage locations using a limited number of acceleration sensors under severe measurement noise condition.

• Structural Engineering and Mechanics
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• v.36 no.6
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• pp.697-714
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• 2010

This paper presents an improved version of the Hilbert-Huang transform (HHT) for the modal evaluation of structural systems or signals. In this improved HHT, a well-designed bandpass filter is used as preprocessing to separate and determine each mode of the signal for solving the inherent modemixing problem in HHT (i.e., empirical mode decomposition, EMD, associated with the Hilbert transform). A screening process is then applied to remove undesired intrinsic mode functions (IMFs) derived from the EMD of the signal's mode. A "best" IMF is selected in each screening process that utilizes the orthogonalization coefficient between the signal's mode and its IMFs. Through mode-by-mode signal filtering, parameters such as the modal frequency can be evaluated accurately when compared to the theoretical value. Time history of the identified modal frequency is available. Numerical results prove the efficiency of the proposed approach, showing relative errors 1.40%, 2.06%, and 1.46%, respectively, for the test cases of a benchmark structure in the lab, a simulated time-varying structural system, and of a linear superimposed cosine waves.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.895-902
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• 2007

Rotating machinery has two typical faults with clearance, one is partial rub and the other is looseness. Due to these faults, non-linear and non-stationary signals are occurred. Therefore, time-frequency analysis is necessary for exact fault diagnosis of rotating machinery. In this paper newly developed time-frequency analysis method, HHT(Hilbert-Huang Transform) is applied to fault diagnosis and compared with other method of FFT, SFFT and CWT. The results show that HHT can represent better resolution than any other method. Consequently, the faults of rotating machinery are diagnosed efficiently by using HHT.

• Earthquakes and Structures
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• v.18 no.4
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• pp.507-517
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• 2020

This study aims to present new frequency-related seismic intensity parameters (SIPs) based on the Hilbert-Huang Transform (HHT) analysis. The proposed procedure is utilized for the processing of several seismic accelerograms. Thus, the entire evaluated Hilbert Spectrum (HS) of each considered seismic velocity time-history is investigated first, and then, a delimited area of the same HS around a specific frequency is explored, for the proposition of new SIPs. A first application of the suggested new parameters is to reveal the interrelation between them and the structural damage of a reinforced concrete frame structure. The index of Park and Ang describes the structural damage. The fundamental frequency of the structure is considered as the mentioned specific frequency. Two statistical methods, namely correlation analysis and multiple linear regression analysis, are used to identify the relationship between the considered SIPs and the corresponding structural damage. The results confirm that the new proposed HHT-based parameters are effective descriptors of the seismic damage potential and helpful tools for forecasting the seismic damages on buildings.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.484-490
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• 2008

For CSLDV, the Chebyshev demodulation (or polynomial) technique and Hilbert transform approach have been used for mode shape reconstruction with harmonic excitation. In this paper, the Hilbert-Huang transform approach was applied as an alternative to impact excitation cases in terms of a numerical approach. The vibration of the tested structure is modeled using impulse response functions. In order to verify this technique, a simply supported beam was chosen as the test rig. With additional innovative steps which are the ideal-band pass filter and the nodal point determination, Hilbert-Huang transformation can be used for a good mode shape reconstruction even in the impact excitation case.