• Journal of the Korean Institute of Telematics and Electronics T
• /
• v.35T no.3
• /
• pp.37-45
• /
• 1998

In this paper, the different frequency component and time informations from an EMI signal are extracted simultaneously using a wavelet transform and the results of transform in the time and frequency domain are analyzed. Frequencies are extracted from the EMI signal by performing the multiresolution analysis using the Daubechies-4 filter coefficients and the time information through the results of wavelet transform. We have tried the correlation analysis to evaluate the results of wavelet transform. We have chosen the optimal wavelet function for an object signal by comparing the transformed results of various wavelet functions and verified the simulation examples of waveform and harmonic analysis using a wavelet transform. We have proved the denoising effect to the EMI signal using the soft thresholding technique.

• Journal of the Korean earth science society
• /
• v.25 no.2
• /
• pp.109-114
• /
• 2004

A wavelet method is applied to the analysis of gravity potential. One scaling function is proposed to generate wavelet. The scaling function is shown to be replaced to the Green’s function in gravity potential. The upward continuation can be expressed as a wavelet transform i.e. convolution with the scaling function. The scaling factor indicates the height variation. The multiscale edge detection is carried by connecting the local maxima of the wavelet transform at scales. The multiscale edge represents discontinuity of the geological structure. The multiscale edge method is applied to gravity data from Masan and Changwon.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.3
• /
• pp.467-472
• /
• 2005

ECG signals are recorded for diagnostic purposes in many clinical situations. Also, In order to permit good clinical interpretation, data is needed at high resolutions and sampling rates. Therefore In this paper, we designed to compression structure using multiple wavelet basis function(SWBF) and compared to single wavelet basis function(SWBF) and discrete cosine transform(DCT). For experience objectivity, Simulation was performed using the arrhythmia data with sampling frequency 360Hz, resolution lIbit at MIT-BIH database. An estimate of performance estimate evaluate the reconstruction error. Consequently compression structure using MWBF has high performance result.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.20 no.6
• /
• pp.501-510
• /
• 2000

Recently, advanced signal analysis which is called "time-frequency analysis" has been used widely in nondestructive evaluation applications. Wavelet transform(WT) and Wigner Distribution are the most advanced techniques for processing signals with time-varying spectra. Wavelet analysis method is an attractive technique for evaluation of material characterization nondestructively. Wavelet transform is applied to the time-frequency analysis of ultrasonic echo waveform obtained by an ultrasonic pulse-echo technique. In this study, the feasibility of noise suppression of ultrasonic flaw signal and frequency-dependent ultrasonic group velocity and attenuation coefficient using wavelet analysis of ultrasonic echo waveform have been verified experimentally. The Gabor function is adopted the analyzing wavelet. The wavelet analysis shows that the variations of ultrasonic group velocity and attenuation coefficient due to the change of material characterization can be evaluated at each frequency. Furthermore, to assure the enhancement of detectability and naw sizing performance, both computer simulated results and experimental measurements using wavelet signal processing are used to demonstrate the effectiveness of the noise suppression of ultrasonic flaw signal obtained from austenitic stainless steel weld including EDM notch.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.9
• /
• pp.31-37
• /
• 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.