• Journal of the Earthquake Engineering Society of Korea
• /
• v.7 no.5
• /
• pp.11-17
• /
• 2003

It is well known that the double integration of measured acceleration records is one of the most difficult signal processing, particularly in the measurements on civil engineering structures, The measured accelerations of civil engineering structures are usually non-stationary and contain non-gaussian low-frequency noises, which can be significant causes of numerical instabilities in double Integration, For the de-noising of this kind of signals, wavelet transform can be very effective because of its inherent processing features for non-stationary signals, In this paper, the de-noising algorithm for the double integration is proposed using the modified wavelet transform, which is extended version of ordinary wavelet transform to process non-gaussian and low-frequency noises, using the median filter concept, The example studies show that the integration can be improved by the proposed method.

• Journal of Urban Science
• /
• v.6 no.2
• /
• pp.49-57
• /
• 2017

A new Fiber Bragg Grating (FBG) wavelength demodulation scheme is studied in the paper, which consists of an improved de-noising method and Gaussian fitting peak searching algorithm. The improved translational invariant wavelet without threshold adjust factor is proposed to get a better de-noising performance for FBG sensor signal and overcome the drawbacks of soft or hard threshold wavelets. In order to get a high wavelength demodulation precision of FBG sensor signal, this de-noising method is designed to combine with Gaussian fitting peak searching algorithm. The simulation results show that the wavelength maximum measurement error is lower than 1pm, and can get a much higher accuracy.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10d
• /
• pp.302-305
• /
• 2006

In this paper, we have proposed a novel method using quantization of wavelet coefficients for secret data communication. First, speech signal is partitioned into small time frames and the frames are transformed into frequency domain using a WT(Wavelet Transform). We quantize the wavelet coefficients and embedded secret data into the quantized wavelet coefficients. The destination regard quantization errors of received speech as seceret dat. As most speech watermark techniques have a trade off between noise robustness and speech quality, our method also have. However we solve the problem with a partial quantization and a noise level dependent threshold. In additional, we improve the speech quality with de-noising method using wavelet transform. Since the signal is processed in the wavelet domain, we can easily adapt the de-noising method based on wavelet transform. Simulation results in the various noisy environments show that the proposed method is reliable for secret communication.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.11 no.4
• /
• pp.13-19
• /
• 2012

There are many dynamic properties in measured end-milling force. So, it is difficult to predict the real static property of end-milling force. Also the behavior of end-milling force is very complex to predict with the measured one. To extract the static property from measured force, it must be filtered and its problem is closely related to a de-noising one. Also this paper presents alternative de-noising method of end-milling force using wavelet filter bank, based on the wavelet transform and its inverse one. In this paper, by comparing the measured force and its wavelet filtered one, the fundamental end-milling force property after wavelet transform is well reviewed and analyzed. This result of wavelet filtering with filter bank shows the static force of end-milling which has severe dynamic properties occurring in entry and exit state of edge emersion into the workpiece.

• Structural Engineering and Mechanics
• /
• v.40 no.1
• /
• pp.13-28
• /
• 2011

An effective method for detection linear flaws in plate structures via two-dimensional discrete wavelet transform is proposed in this study. The proposed method was applied to a four-fixed supported rectangular plate containing damage with arbitrary length, depth and location. Numerical results identifying the damage location are compared with the actual results to demonstrate the effectiveness of the proposed method. Also, a wavelet-based method presented for de-noising of mode shape of plate. Finally, the performance of the proposed method for de-noising and damage identification was verified using experimental data. Comparison between the location detected by the proposed method, and the plate's actual damage location revealed that the methodology can be used as an accessible and effective technique for damage identification of actual plate structures.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.12
• /
• pp.1185-1192
• /
• 2015

In this paper, a study of advanced sound source localization is conducted by eliminating the noise of the sound source using the discrete wavelet transform. And experiments are conducted to evaluate the performance of the proposed system that the mobile robot follows sound source stably. In addition, we compare the position estimation performance by applying a discrete wavelet transform to improve the reliability of the sound signal. The experimental results reveal that the de-nosing filter which removes the noise component in sound source can make the performance of position estimation more precisely and help the mobile robot distinguish the objective sound source clearly.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.28 no.3
• /
• pp.84-90
• /
• 2014

The partial discharge of Cast-resin Transformer has a difficulty to be analyzed, because it is an abnormal condition signal of which stochastic characteristics varies with time variance. In this study, background noise coming from the outside of the cast-resin transformers through ground wire can be removed and only a discharge signal of which defects are simulated can be obtained, using the wavelet transform method, which is a time-frequency domain analysis technique. As a result, it was confirmed that de-noising using the SWT technique is the best efficient among three methods of the wavelet transform techniques.

• Nuclear Engineering and Technology
• /
• v.31 no.2
• /
• pp.192-201
• /
• 1999

This paper proposes an improved signal processing strategy for accurate feedwater flowrate estimation in nuclear power plants. It is generally known that ∼2% thermal power errors occur due to fouling Phenomena in feedwater flowmeters. In the strategy Proposed, the noises included in feedwater flowrate signal are classified into rapidly varying noises and gradually varying noises according to the characteristics in a frequency domain. The estimation precision is enhanced by introducing a low pass filter with the wavelet analysis against rapidly varying noises, and an autoassociative neural network which takes charge of the correction of only gradually varying noises. The modified multivariate stratification sampling using the concept of time stratification and MAXIMIN criteria is developed to overcome the shortcoming of a general random sampling. In addition the multi-stage robust training method is developed to increase the quality and reliability of training signals. Some validations using the simulated data from a micro-simulator were carried out. In the validation tests, the proposed methodology removed both rapidly varying noises and gradually varying noises respectively in each de-noising step, and 5.54% root mean square errors of initial noisy signals were decreased to 0.674% after de-noising. These results indicate that it is possible to estimate the reactor thermal power more elaborately by adopting this strategy.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.6
• /
• pp.1487-1496
• /
• 2013

In this paper, a novel algorithm for PD localization in power transformers based on wavelet de-noising technique and energy criterion is proposed. Partial discharge is one of the main failures in power transformers. The localization of which could be very useful for maintenance systems. Acoustic signals due to a PD event are transient, irregular and non-repetitive. So wavelet transform is an efficient tool for this signal processing problem that gives a time-frequency demonstration. First, different wavelet based de-noising methods are analyzed. Then, a reasonable structure for threshold value determining and applying manner on signals is presented. Evaluated errors are good evidences for choices. Next, applying the elimination low energy frequency bands is discussed and developed as a de-noising method. Time differences between signals are used for PD localization. Different ways in time arrival detection are introduced and a novel approach in energy criterion method is presented. At the end, the quality of algorithm is verified through the different assays in lab.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.893-897
• /
• 2008

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper examines an effective method of minimizing the drift on the heading angle that relies solely on integration of rate signals from a gyro. The main idea of the proposed approach is to use wavelet de-noising filter in order to reduce random noise which affects short-term performances. The proposed method was applied to Epson XV3500 gyro and the performances are verified by the comparisons with an existing commercial gyro module of vacuum cleaning robots.