• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.96-102
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• 2005

Acoustic Emission(AE) technique has been applied to not only material characterization evaluation but also on-line monitoring of the structural integrity. The AE source location technique is very important to identify the source, such as crack, leak detection. Since the AE waveforms obtained from sensors are very difficult to distinguish the defect signals, therefore, it is necessary to consider the signal analysis of the transient wave-form. In this study, we have divided the region of interest into a set finite elements, and calculated the arrival time differences between sensors by using the velocities at every degree from 0 to 90. A new technique for the source location of acoustic emission in fiberboard plates has been studied by introducing Wavelet Transform(WT) do-noising technique. WT is a powerful tool for processing transient signals with temporally varying spectra. If the WT de-noising was employed, we could successfully filter out the errors of source location in fiberboard plates by arrival time difference method. The accuracy of source location appeared to be significantly improved.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.2
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• pp.203-207
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• 2012

Purpose: Electroretinogram(ERG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of retinal-related diagnosis with removing signal noise. Methods: Sampling signal was made with generating 60 Hz noise and white noise. The noise were removed using wavelet transforms and bandpass filter. De-noising frequency was compared with Fourier transform spectrum. Removed noises were compared numerically using SNR(signal to noise ratio). Results: The result compared Fourier transform spectrum was showed that 60 Hz noise removed completely and most of white noise was removed by wavelet transforms. 60 Hz and the white noise remained using bandpass filters. The result compared SNR showed that wavelet transforms was 22.8638 and bandpass filter was 4.0961. Conclusions: Wavelet transform showed less signal distortion in removing noise. ERG signal is expected to improve the accuracy of retinal-related diagnosis.

• Proceedings of the Korean Nuclear Society Conference
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• 2002.10a
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• pp.62.2-62
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• 2002

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.367-368
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• 2007

In this paper, we propose a new de-noising algorithm for 2 dimensional image using discrete wavelet transform. The proposed algorithm consists of edge detection in spatial domain, zero-tree estimation, subband estimation, and shrinkage algorithm. The results from it shows that the denoised image which Is damaged by 20% gaussian noise has 28dB quality for the original one.

• Journal of the Korea society of information convergence
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• v.6 no.2
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• pp.45-49
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• 2013

Electrocardiogram(ECG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of cadiac disease diagnosis with removing signal white-noise. Sampling signal was made with generating white-noise. The noise were removed using wavelet transforms and thresholding. Removed noise were compared numerical using SNR(signal to noise ratio). The results compared SNR showed that SURE method was 5.931, 4.9301 in 3, 5dB noise, uninversal was 3.6590, 1.9698 in 7, 9dB noise. De-noising by Thresholding removed noise effectively. ECG signal is expected to improve the accuracy of cadiac desease dianosis.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.341-348
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• 2013

A location estimation algorithm based on the sea-surface beacon is proposed in this paper. The beacon is utilized to provide ultrasonic signals to the underwater vehicles around the beacon to estimate precise position of underwater vehicles (ROV, AUV, Diver robot), which is named as USBL (Ultra Short Baseline) system. It utilizes GPS and INS data for estimating its position and adopts DWT (Discrete Wavelet Transform) de-noising filter and UKF (Unscented KALMAN Filter) elaborating the position estimation. The beacon system aims at estimating the precise position of underwater vehicle by using USBL to receive the tracking signals. The most important one for the precise position estimation of underwater vehicle is estimating the position of the beacon system precisely. Since the beacon is on the sea-waves, the received GPS signals are noisy and unstable most of times. Therefore, the INS data (gyroscope sensor, accelerometer, magnetic compass) are obtained at the beacon on the sea-surface to compensate for the inaccuracy of the GPS data. The noises in the acceleration data from INS data are reduced by using DWT de-noising filter in this research. Finally the UKF localization system is proposed in this paper and the system performance is verified by real experiments.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.505-508
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• 2005

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.381-387
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• 2009

The end-milling force behaviour is very complex and it is related to a de-noising phenomenon, so it is very difficult to detect and diagnose this static cutting force phenomenon. This paper presents a new method of filtering of end-milling force in end-milling operation using filter bank technique, based on the wavelet transform. In this paper by comparing the history of end-milling force using wavelet filtering the fundamental end-milling property of the wavelet transform is well reviewed and analyzed. This result of wavelet transform using filter bank shows the possible static prediction of end-milling force with severe dynamic properties such as chatter in end-milling operation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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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.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.309-314
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• 2003

Impact Echo method has been successful in detecting a variety of defects in concrete structure. This study has the objectives to show important aspects of applying the Discrete Wavelet Transform(DWT) to signal processing of Modified Impact Echo(ModIE) Measurement systems and to the understanding of the seismic wave propagation. The data of ModIE were processed by DWT and compared with the results of conventional ModIE Analysis. Although it is inconsistent in the evaluated thickness of concrete lining, the DWT provides the features of separation, synthesis and de-noising in the original signal. The application of technique by wavelet was explained numerically with ABAQUS and performed experimentally with a real scale model in this work. Further works on the possible ways for creating new mother wavelet are specially needed for the enhancement of seismic signal analysis.