• 한국정밀공학회지
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• 제13권9호
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• pp.31-37
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• 1996

This Paper is concerned with effective signal identification method for tool breakage and micro chipping using discrete wavelet transform of feed motor current in milling operations. The wavelet transform uses an analyzing waveletfunction which is localized in both frequency and time domain to detect subtle time localized changes in input signals. The changing pattern of wavelet coefficient is continuously compared to detect tool breakage and micro chipping over one spindle revolution. The results indicate that the wavelet transform can identify tool failure with much greater sensi- tivity than the time domain monitoring and frequency domain monitoring such as FFT. Experimental results are presented to support the proposed scheme.

• 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.

• 한국생산제조학회지
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• 제8권1호
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• pp.135-141
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• 1999

Recently, advance signal analysis which is called "Time-Frequency Analysis" has been developed. Wavelet and Wigner Distribution are used to the method. Wavelet transform(WT) is applied to time-frequency analysis of waveforms obtained by an ultrasonic pulse-echo technique. The Gabor function is adopted as the analyzing wavelet. Wavelet analysis method is an attractive technique for evolution of material characterization evoluation. In this paper, the feasibility of suppression of ultrasonic background noise signal using WT has been presented. These results suggest that ultrasonic background noise ginal can be suppressed and enhanced even for SNR of 20.8 dB. This property of the WT is extremely useful for the detecting flaw echos embedded in background noise.und noise.

• 한국기계가공학회지
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• 제1권1호
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• pp.29-37
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the diagnosis of grinding conditions in grinding process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. STD11 workpiece was 85 times of machined pieces cut by the WA wheel and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At dressing time, the approximation signals were slowly increased and 45 machined times noticed dressing time.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.1063-1066
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• 2002

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• 한국정밀공학회지
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• 제19권12호
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• 한국정보통신학회논문지
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• 제23권3호
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• pp.291-298
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• 2019

본 논문에서는 디지털 홀로그램을 효율적으로 분해하기 위해서 다양한 웨이블릿 함수들을 이용한 프레넬릿 변환 방식을 제안하였다. 제안한 웨이블릿 함수 기반의 프레넬릿 변환들을 구현한 후에 디지털 홀로그램에 적용하고 계수들의 에너지에 대한 특성을 분석한다. 구현한 웨이블릿 함수 기반의 프레넬릿 변환은 광학적으로 획득되거나 혹은 컴퓨터 생성 홀로그램 기법으로 생성된 홀로그램의 복원과 처리에 매우 적합하다. 스플라인 함수의 특성을 분석한 이후에 이를 기반으로 하는 웨이블릿 다해상도 해석 방법에 대해서 살펴본다. 이러한 과정을 통해 광학적 간섭 현상을 통해 생성된 프린지 패턴을 효과적으로 분해할 수 있는 변환 도구를 제안하였다. 다양한 분해 특성을 갖는 웨이블릿 함수기반의 프레넬릿 변환을 구현하였고 이를 이용하여 프린지 패턴을 분해한 결과들을 보인다. 결과를 살펴보면 랜덤 위상의 포함여부에 따라 계수들의 에너지 분포가 크게 다르다는 것을 확인할 수 있다.

• 한국기계가공학회지
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• 제9권5호
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• pp.1-6
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• 2010

The wavelet transform is a popular tool for studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.640-641
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• 2007

In this paper, the discrete wavelet transform (DWT) was applied a fault detection of a synchronous generator being superior to a transient state signal analysis and being easy to real time realization. The fault signals after executing a terminal fault modeling collect using a MATLAB package, and calculate the wavelet coefficients through the process of a multi-level decomposition (MLD). The proposed algorithm of a fault detection of a generator using Daubechies WT (wavelet transform) was executed with a C language for the commend line function and for the real time realization after analyzing MATLAB's graphical interface.

• Journal of applied mathematics & informatics
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• 제17권1_2_3호
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• pp.747-757
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• 2005

A physical variable is customarily thought of as a function. Another way of describing a physical variable is to specify it as a functional, whose special type is called a distribution. It turns out that the distribution concept provide a better mechanism for analyzing certain physical phenomena than does the function concept. By using wavelets with high regularity we give a resolution of functions with slow growth.