• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.546-547
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• 2012

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.739-742
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• 2007

In the step processing multimedia information signals transmitted by a variety of mediums, noises are generated by the internal or exterior causes of systems and these noises degrade the perception about information signals. Therefore, in order to remove noises and restore signals a great number of researches have been progressed and recently, many noise removal methods using time-frequency localization of wavelet have been applied in wide applications. Moreover, when two wavelet bases are designed to accomplish the Hilbert transform pair, wavelet can be efficiently applied to detect characteristics of signals. Therefore, in this paper, in order to restore the corrupted signal by noises, a noise removal algorithm using the Hilbert transform pair of wavelet was proposed.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.2
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• pp.62-70
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• 2007

The aiming ability is a to improve accuracy performance of the firing vehicle. This paper describes the detection method of chatter vibration using disturbance acceleration in the pointing structure. In order to analysis vibration trends of the pointing system occurred during vehicle drive, acceleration data was processed by using data processing algorithm with moving average and Hilbert transform. Specific mode constants of acceleration were obtained under various disturbances. Vehicle velocity, road condition, property of pointing structure were considered as factors which make change of vibration trend in vehicle dynamics. Finally, back propagation neural networks have been applied to the pattern recognition for the classification of vibration signal in various driving conditions. Results of signal processing were compared and analysed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.179-190
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• 2017

Hand Accelerometers are widely used to detect human motion patterns in real-time. It is essential to reliably identify which type of activity is performed by human subjects. This rests on having accurate template of each activity. Many human activities are represented as a set of multiple time-series data from such sensors, which are mostly non-stationary and non-linear in nature. This requires a method which can effectively extract patterns from non-stationary and non-linear data. To achieve such a goal, we propose the method to apply Hilbert-Huang Transform which is known to be an effective way of extracting non-stationary and non-linear components from time-series data. It is applied on samples of accelerometer data to determine its effectiveness.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.414-419
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• 2003

There are some methods fur extracting mode shapes from a continuously scanned data such as a modulation, Chebyshev polynomial, and Hilbert approach. In this paper, Chebyshev and Hilbert approaches were investigated through the numerical experiment first. As some experimental parameters were altered with small quantities, data were checked and plotted. From those results, the effects of unexpected parameters will be configured. And then, it will be actually helpful to select the proper method for specific testing environments.

• 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.

• 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.

• 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.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.567-570
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• 1988

This paper describes the design of FIR filtering DSP-chip that can be operated without programming. The proposed DSP-chip has not only the improvement of execution time but also selectivity of filter length from N=1 to N=128. Hilbert Transformer can be designed from this chip. FIR filter system is composed of Data memory/Control Unit, external memory and multiplier-accumulator. Data memory/Control Unit is laid out in this paper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.10a
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• pp.21-27
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• 1993

매개변수가진에 종속되는 현의 횡방향진동을 시간영역에서 필터작업, 힐버트 변환과 순간주파수 개념을 도입하여 해석함으로서 종방향의 순간진동변위를 추정하는 방법이 제시되었다. 그리고, 실험을 통하여 이론의 타당성을 검증 하였다. 또한, 모의 실험의 결과 일반적인 현구동계에 있어서는 넓은 적용변 수의 선\ulcorner영역에서 종변위가 횡변위와 분리(decoupling) 되어서 공간적으로 길이에 따르는 선형적인 증가성과 시간적으로 조화적인 주기성을 가진다는 것을 확인함으로서 임의의 위치에서의 종변위를 파악함이 가능하였다.