• Journal of Information Processing Systems
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• v.14 no.4
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• pp.941-947
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• 2018

Since the amplitudes of spin echo train in nuclear magnetic resonance logging (NMRL) are small and the signal to noise ratio (SNR) is also very low, this paper puts forward an improved de-noising algorithm based on wavelet transformation. The steps of this improved algorithm are designed and realized based on the characteristics of spin echo train in NMRL. To test this improved de-noising algorithm, a 32 points forward model of big porosity is build, the signal of spin echo sequence with adjustable SNR are generated by this forward model in an experiment, then the median filtering, wavelet hard threshold de-noising, wavelet soft threshold de-noising and the improved de-noising algorithm are compared to de-noising these signals, the filtering effects of these four algorithms are analyzed while the SNR and the root mean square error (RMSE) are also calculated out. The results of this experiment show that the improved de-noising algorithm can improve SNR from 10 to 27.57, which is very useful to enhance signal and de-nosing noise for spin echo train in NMRL.

• Nuclear Engineering and Technology
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• v.39 no.3
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• pp.221-230
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• 2007

Wavelet theory was applied to detect a singularity in a reactor power signal. Compared to Fourier transform, wavelet transform has localization properties in space and frequency. Therefore, using wavelet transform after de-noising, singular points can easily be found. To test this theory, reactor power signals were generated using the HANARO(a Korean multi-purpose research reactor) dynamics model consisting of 39 nonlinear differential equations contaminated with Gaussian noise. Wavelet transform decomposition and de-noising procedures were applied to these signals. It was possible to detect singular events such as a sudden reactivity change and abrupt intrinsic property changes. Thus, this method could be profitably utilized in a real-time system for automatic event recognition(e.g., reactor condition monitoring).

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.828-829
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• 2015

본 논문은 몰드 변압기의 PD(Partial Discharge) 발생 여부를 판단하기 위해 Wavelet Transform을 이용한 PD 신호의 De-Noising에 관한 연구이다. PD는 변압기 고장사고 중 가장 판단하기 어렵고, 예방 및 진단 시 적은 항목의 검사 항목을 통해 관리되어진다. 따라서 보다 정확하게 PD 발생 여부를 판단하는 것이 중요하다. 본 논문에서는 몰드 변압기의 PD 신호를 측정하고, 취득한 신호를 Wavelet Transform을 이용한 De-Noising을 수행하고 몰드 변압기의 PD 발생여부에 대해 확인하는 방법에 대한 연구를 수행하였다.

• The Journal of the Acoustical Society of Korea
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• v.25 no.7
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• pp.333-338
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• 2006

This paper proposes an improved do-noising method using multi-thresholding function based on translation-invariant (W) wavelet proposed by Donoho et al. for underwater radiated noise measurement. The traditional wavelet thresholding de-noising method causes Pseudo-Gibbs phenomena near singularities due to discrete wavelet transform. In order to suppress Pseudo-Gibbs Phenomena, a do-noising method combining multi-thresholding function with the translation-invariant wavelet transform is proposed in this paper. The multi-thresholding function is a modified soft-thresholding to each node according to the discriminated threshold so as to reject かon external noise and white gaussian noise. It is verified by numerical simulation. And the experimental results are confirmed through sea-trial using multi-single sensors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.914-916
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• 2016

The noise in a power signal degrades the detection rate of the power quality (PQ) event signals. We present a new wavelet de-noising technique for PQ event detection that employs the correlation-based thresholding instead of the wavelet-scale-based thresholding of existing schemes. The simulation results show that the proposed scheme is more robust to Gaussian and impulsive noisy conditions and has further improved detection ratio than existing schemes.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.67-72
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• 1996

Wavelets are localized in space and in frequency. This localization properties result from the multiresolution analysis of wavelets. The wavelet transform can be used to detect singularity of dynamic systems after the signal is de-noised. We applied the wavelet transform decomposition and do-noising procedures to the Hanaro dynamics consisting of 39 nonlinear differential equation plus Gaussian noise. The numerical tests demonstrate that the wavelet transform de-noising is effective for detection of the abrupt reactivity change and computationally efficient. Thus this wavelet theory could be profitably utilized in a real-time system for automatic event recognition (e.g., reactor condition monitoring).

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.490-500
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• 2000

A new technique for the source location of acoustic emission (AE) in plates whose thichness are close to or thinner than the wavelength has been studied by introducing wavelet transform de-noising technique. The detected AE signals were pre-processed using wavelet transform to be decomposed into the low-frequency, high-amplitude flexural components and the high-frequency, low-amplitude extensional components. If the wavelet transform de-noising was employed, we could successfully filter out the extensional wave component, one of the critical errors of source location in plates by arrival time difference method. The accuracy of source location appeared to be significantly improved and independent of the setting of gain and threshold, plate thickness, sensor-to-sensor distance, and the relative position of source to sensors. Since the method utilizes the flexural component of relatively high amplitude, it could be applied to very large, thin-walled structures in practice.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.94-102
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• 2007

In de-noising, it is wellknown that wavelet-thresholding algorithm shows near-optimal performances in the minimax sense. However, the wavelet-thresholding algorithm is difficult in realization it on hardware, such as FPGA, because of wavelet function complexity. In this paper, we present a new do-noising technique with the binary tree structured filter bank, which is based on the signal power ratio of each subbands to the total signal power. And we realize it on FPGA. For simple realization, the filter banks are designed by Hadamard transform coefficients. The simulation and hardware experimental results show that the performance of the proposed method is similar with that of soft thresholding de-noising algorithm based on wavelets, nevertheless it is simple.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1330-1341
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• 2010

Power analysis (PA) is known as a powerful physical attack method in the field of information security. This method uses the statistical characteristics of leaked power consumption signals measured from security devices to reveal the secret keys. However, when measuring a leakage power signal, it may be easily distorted by the noise due to its low magnitude values, and thus the PA attack shows different performances depending on the noise level of the measured signal. To overcome this vulnerability of the PA attack, we propose a noise-reduction method based on wavelet de-noising. Experimental results show that the proposed de-noising method improves the attack efficiency in terms of the number of signals required for the successful attack as well as the reliability on the guessing key.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.271-280
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• 2004

This paper presents a new iterative image restoration algorithm with removal of boundary/object-oriented ringing, The proposed method is based on CGM(Conjugate Gradient Method) iterations with inter-wavelet shrinkage. The proposed method provides a fast restoration as much as CGM, while having adaptive do-noising and do-ringing by using wavelet shrinkage. In order to have effective do-noising and do-ringing simultaneously, the proposed method uses a space-dependent shrinkage rule. The improved performance of the proposed method over more traditional iterative image restoration algorithms such as LR(Lucy-Richardson) and CGM in do-noising and do-ringing is shown through numerical experiments.