• 한국정보전자통신기술학회논문지
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• 제2권2호
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• pp.29-36
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• 2009

비선형적인 위상 변화를 지닌 비정상(non-stationary)신호는 레이더(Radar), 통신(telecommunication), 생체공학, 지질탐사, 음향 등 여러 분야에서 쉽게 접하는 신호이다. 비정상신호는 일반적으로 시간에 따라 신호의 물리적 특성이 변화하는 신호를 의미하며, 순간 주파수는 신호의 특정시간에 해당하는 신호의 주파수를 의미한다. 이 논문에서는 순간 주파수를 결정하기 위한 연속 웨이브렛 변환의 적용에 대하여 논하였다.

• 전기학회논문지
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• 제63권2호
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• pp.291-296
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• 2014

Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of weak stationarity. The purpose of this study is to analyze the accuracy of the Run-test, modified Run-test, RA(reverse arrangement)-test, and modified RA-test for assessing surface EMG signal stationarity. Six stationary and three non-stationary signals were simulated by using sine wave, AR(autoregressive) modeling, and real surface EMG. The simulated signals were tested for stationarity using nine different methods of Run-test and RA-test. The results showed that the modified Run-test method2 (mRT2) classified exactly the surface EMG signals by stationarity with 100% accuracy. This finding indicates that the mRT2 may be the best way for assessing stationarity in surface EMG signals.

• 응용통계연구
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• 제22권3호
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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.

• 한국산업정보학회논문지
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• 제11권3호
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• pp.15-19
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• 2006

비백색잡음(non-white noise)인 잔향(reverberation)이 신호탐지(signal detection)의 주 방해신호인 천해 능동소나(active sonar) 환경에서의 표적탐지는 선백색화기(pre-whitener)를 사용하여 수신신호를 백색화한 후 백색잡음에서 최적 탐지기(optimum detector)인 정합필터를 사용한다. 그러나 이 방법은 잔향이 비정상(non-stationary) 특성을 가지기 때문에 구현이 매우 힘들다. 기존의 연구에 따르면 이러한 잔향은 지역적 정상상태(local stationary).라고 가정할 수 있다. 본 논문에서는 먼저 잔향신호의 지역적 정상상태의 범위를 추정(estimation)하고, 이 추정을 바탕으로 비백색 잔향신호 환경에서 선백색화 블록 정규화 정합필터(pre-whitening block normalized matched filter)의 성능을 개선할 수 있는 선백색화 기법을 제안하였다. 제안된 잔향신호의 백색화 기법은 표적신호 전 후의 잔향신호를 사용하여 처리블록(processing block)을 백색화하기 때문에 기존의 백색화 기법보다 우수한 성능을 보였다. 제안된 백색화 기법을 이용한 탐지기의 성능을 평가하기 위해 우리나라 인근해역에서 실측된 데이터를 이용하여 컴퓨터 모의실험을 수행하였다. 모의실험 결과 제안된 기법을 사용한 탐지기는 기존의 백색화 기법을 사용한 탐지기보다 우수한 탐지선응을 보였다.

• 대한전자공학회논문지SP
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• 제47권5호
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• pp.222-228
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• 2010

본 논문에서는 비정상적인 배경 잡음 환경에서 음성향상을 위한 신호의 스펙트럼 변이 (Spectral Deviation)을 적용한 Soft Decision 기반의 잡음전력 수정 기법을 제안한다. 기존의 Soft Decision 기반의 잡음전력 추정에 있어서 잡음신호의 정상성(Stationarity)을 가정한 스무딩 파라미터를 사용하여 잡음전력을 추정하고 갱신하였지만, 잡음신호의 주파수적인 특성이 상대적으로 빠르게 변하는 비정상적인 환경에서는 강인하지 못한 단점을 가지게 된다. 본 논문에서는 신호의 스펙트럼 변이를 추정하여 정상적인 잡음 환경과 비정상적인 잡음 환경에 따라 적응적으로 잡음전력을 추정하고 갱신하여 잡음신호에 의해 오염된 음성신호를 향상시킨다. 제안된 알고리즘은 다양한 배경 잡음 환경에서 객관적인 음질측정 방법인 ITU-T P.862 perceptual evaluation of speech quality (PESQ)에 의해서 평가되었으며, 기존의 Soft Decision 기반의 음성 향상 기법과 비교하여 보다 향상된 성능을 보여주었다.

• 대한기계학회논문집A
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• 제30권9호
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• pp.1154-1159
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• 2006

In this paper, time-frequency analysis and multi-dimensional spectral analysis methods are applied to source identification and diagnostic of non-stationary sound vibration signals. By checking the coherences for concerned time, this simulation is very well coincident to expected results. The proposed method analyzes the signal instantaneously in both time and frequency domains. The MDSA (Multiple Dimensional Spectral Analysis) analyzes the signal in the plane of instantaneous time and instantaneous frequency at the same time. And it was verified by using the 1500cc passenger car which is accelerated from 70Hz to 95Hz in 4 seconds, the proposed method is effective in determining the vehicle diagnostic problems.

• International Journal of Precision Engineering and Manufacturing
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• 제6권4호
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• pp.26-30
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• 2005

A rotor run-up or run-down process provide more useful information for modal analysis than normal operation conditions. A traditional difficulty associated with rotor run-up or run-down analysis is the non-stationary nature of vibration data. This paper compares Short-Time Fourier Transform (STFT) and the wavelets analysis in these non-stationary signal analyses. An Adaptive Wavelet Analysis (AWT) is proposed to analyze these signals. Although simulations and experiments in a simple rotor-bearing system show that both STFT and AWT can be used to analyze non-stationary vibration signals in rotor dynamics, proposed AWT provides better results than STFT analysis. From the amplitude-frequency curve obtained by AWT, the modal frequency and damping ratio are calculated. This paper also analyzes the characteristics of signals when the shaft touches the outer hoop in a run-up process. The AWT can give a good result in this complex dynamic analysis of the touching process.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.1009-1012
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• 2004

Recently, the concern on sound qualify (SQ) is on the steep increase in the fields of vehicle and home appliance and over the fast few decades a considerable number of studies have been conducted on SQ evaluation. As a result, basic procedure for SQ evaluation has been already suggested. Although most interesting sounds have time-varying features, however, little is known about their SQ evaluation. The purpose of this study is to systematize a method for SQ evaluation of non-stationary sound. For this, various listening tests procedure for non-stationary sound is introduced and it is attempted to find out correlation between various SQ metrics and subjective data obtain from listening test. Booming of car interior noise in acceleration is used as an example and finally, representative value is obtained for the interesting sensation of non-stationary sound.

• Journal of Biosystems Engineering
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• 제26권6호
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• pp.503-508
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• 2001

In this paper, time-fiequency analysis and multi-dimensional spectral analysis methods are applied for source identification and diagnosis of non-stationary sound/vibration signals. Sound or vibration problems of general vehicle and agricultural machinary are under 500 Hz. So We used linearly increased chirp signals under 500 Hz. By checking the coherences on concerned time, fur time-variant non-stationary signals, this simulation it very well coincident to expected results.

• 한국정밀공학회지
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• 제22권10호
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• pp.80-89
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• 2005

In this paper, time-frequency analysis using wavelet packet transform and advanced-MDSA (Multiple Dimensional Spectral Analysis) which based on wavelet packet transform is applied fur fault source identification and diagnosis of early detection of fault non-stationary sound/vibration signals. This method is analyzing the signal in the plane of instantaneous time and instantaneous frequency. The results of ordinary coherence function, which obtained by wavelet packet analysis, showed the possibility of early fault detection by analysis at the instantaneous time. So, by checking the coherence function trend, it is possible to detect which signal contains the major fault signal and to know how much the system is damaged. Finally, It is impossible to monitor the system is damaged or undamaged by using conventional method, because crest factor is almost constant under the range of magnitude of fault signal as its approach to normal signal. However instantaneous coherence function showed that a little change of fault signal is possible to monitor the system condition. And it is possible to predict the maintenance time by condition based maintenance for any stationary or non-stationary signals.