• Proceedings of the KSME Conference
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• 2001.06b
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• pp.392-397
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• 2001

This paper concerns on modal analysis of mechanical structures by using a continuous scanning laser Doppler vibrometer. In modal analysis the Hilbert transform based approach is superior to the Fourier transform based approach because of its fine accuracy and its flexible experimental settings. In this paper the Hilbert transform based approach is extended to measure area mode shape data of a structure by simply modifying the scanning pattern ranging the entire surface of the structure. The effectiveness of this proposed method is illustrated along with results of numerical simulation for a rectangular plate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.700-705
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• 2008

In this paper, we propose object classification algorithm for real-time surveillance system. We have approached this problem using silhouette-based template matching. The silhouette of the object is extracted, and then it is compared with representative template models. Template models are previously stored in the database. Our algorithm is similar to previous pixel-based template matching scheme like Hausdorff Distance, but we use 1D image array rather than 2D regions inspired by Hilbert Path. Transformation of images could reduce computational burden to compute similarity between the detected image and the template images. Experimental results show robustness and real-time performance in object classification, even in low resolution images.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.331-337
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• 2013

Acoustic Emission 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 bearing problems and Wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet. Therefore, in this paper two methods which are Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94% classification accuracy with the parameter of the RBF 0.08, 12 feature selection.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.443-448
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• 2000

In this paper, we propose a novel adaptive feedforward controller for periodic disturbance and noise cancellation, with a frequency tracking capability. It can be added to an existing feedback control system without altering the original closed-loop characteristics, which is based on adaptive algorithm. We introduce novel algorithm "Constrained AFC(adaptive feedforward controller) algorithm" that increase the convergence region regardless of the delay in the closed loop system. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the coefficients become time invariant. The proposed algorithm not only estimate the magnitude and phase of the tonal disturbance and noise but also track the frequency of the tone, which changes in quasi-static manner. The frequency tracking algorithm uses the instantaneous frequency approach based on Hilbert transform. A number of computer simulations have been carried out in order to demonstrate the effectiveness of proposed method under various conditions.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.15-26
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• 2015

In this paper, amplitude and phase difference patterns for theta and alpha bands of the Evoked Potential(EP) in relation to perform a task at visual stimulus were analyzed using the Empirical mode decomposition(EMD). The EMD is applied to decompose EP signals with task-related sub-frequency band signals. Intrinsic mode function was implied in Hilbert transform and instantaneous amplitude and phase differences of theta and alpha were derived from Hilbert transformed EP. In a task status, large amplitude for both bands was observed at P2, N2, and P3 points as well as maximum phase difference was observed at N1 and P2. We confirmed that both bands are associated with a task at visual stimulus, and less associated with fixation. The proposed method enhances the time and frequency resolution in comparison with band-pass filter method which observed different phase results according to conditions.

• Journal of the Korean GEO-environmental Society
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• v.18 no.4
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• pp.13-21
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• 2017

Ballasted track has been used as track system for more than 100 years. Ballasted track has advantages of low construction cost, flexible maintenance, low noise and vibration, and so on. However, ballasted track leads to continuous settlement which causes maintenance. Recently, increase in speed, traffic volume, and weight of train requires more frequent maintenance. Fouling, well-known phenomenon of accumulation of fine materials due to intrusion of subgrade and breakage of ballast materials, expedites the settlement (i.e., irregular settlement) of track. Ground Penetrating Radar (GPR) can be one of non-destructive tools that can evaluate fouling level of ballast. In this paper, a gain function based on the attenuation characteristics of ballast material is suggested in conjunction with Hilbert transform. Lab box tests and full-scale tests indicate that the suggested method reasonably classifies clean, fouled layers, and subgrade. However, additional study to eliminate effect of sleeper and to include the scattering features of the electromagnetic wave in ballast voids should be required in order to enhance the accuracy.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.438-449
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• 2009

To analyze reception environments of ATSC Digital TV, CIR (Channel Impulse Response) analysis systems are widely applied. The receiving performances of conventional CIR analysis systems are not as good as those of commercial state-of-the-art receivers. There are difficulties in measuring and analyzing reception problems caused by multi-path interferences. To solve these problems, commercial DTV chip sets embedded CIR analysis system is proposed. Generally, commercial chip sets provide baseband (In-phase) channel data and field or segment sync data. For more precise analysis of measured I channel data, it is necessary to extract Q (quadrature) channel data components as well. This paper presents the technical requirements of CIR analysis system for DTV. In order to satisfy such requirements and measure more accurate magnitude and phase of CIR, a method to derive the quadrature data from the measured in-phase channel data is proposed. The proposed channel analysis system is implemented with a commercial DTV chip set and expedites the data analysis for use on DTV field test vehicles. Computer simulation and laboratory test results are provided to demonstrate the performance of the proposed channel analysis system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.45-54
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• 2007

Time/frequency analysis has been extensively used in biomedical signal processing. By extracting some essential features from the electro-physiological signals, these methods are able to determine the clinical pathology mechanisms of some diseases. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. In this paper, we develop a new signal processing method using Hilbert-Huang Transform to perform analysis of the nonlinear and non-stationary ventricular fibrillation(VF). Hilbert-Huang Transform combines two major analytical theories: Empirical Mode Decomposition(EMD) and the Hilbert Transform. Hilbert-Huang Transform can be used to decompose natural data into independent Intrinsic Mode Functions using the theories of EMD. Furthermore, Hilbert-Huang Transform employs Hilbert Transform to determine instantaneous frequency and amplitude, and therefore can be used to accurately describe the local behavior of signals. This paper studied for Return Of Spontaneous Circulation(ROSC) and non-ROSC prediction performance by Support Vector Machine and three parameters(EMD-IF, EMD-FFT) extracted from ventricular fibrillation ECG waveform using Hilbert-Huang transform. On the average results of sensitivity and specificity were 87.35% and 76.88% respectively. Hilbert-Huang Transform shows that it enables us to predict the ROSC of VF more precisely.

• Journal of KIISE
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• v.42 no.1
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• pp.97-106
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• 2015

Recently, research on database encryption for data protection and query result authentication methods has been performed more actively in the database outsourcing environment. Existing database encryption schemes are vulnerable to order matching and counting attack of intruders who have background knowledge of the original database domain. Existing query result integrity auditing methods suffer from the transmission overhead of verification object. To resolve these problems, we propose a group-order preserving encryption index and a query result authentication method based on the encryption index. Our group-order preserving encryption index groups the original data for data encryption and support query processing without data decryption. We generate group ids by using the Hilbert-curve so that we can protect the group information while processing a query. Finally, our periodic function based data grouping and query result authentication scheme can reduce the data size of the query result verification. Through performance evaluation, we show that our method achieves better performance than an existing bucket-based verification scheme, it is 1.6 times faster in terms of query processing time and produces verification data that is 20 times smaller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.99-105
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• 2009

Crack detection method of a rotating blade was suggested in this paper. A rotating blade was modeled with a cantilever beam connected to a hub undergoing rotating motion. The existence and the location of crack were able to be recognized from the vertical response of end tip of a rotating cantilever beam by employing Discrete Hidden Markov Model (DHMM) and Empirical Mode Decomposition (EMD). DHMM is a famous stochastic method in the field of speech recognition. However, in recent researches, it has been proved that DHMM can also be used in machine health monitoring. EMD is the method suggested by Huang et al. that decompose a random signal into several mono component signals. EMD was used in this paper as the process of extraction of feature vectors which is the important process to developing DHMM. It was found that developed DHMMs for crack detection of a rotating blade have shown good crack detection ability.