• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.63-64
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• 2013

Induction motors' faults detection is almost a popular topic among researchers. Monitoring the output of motors is a key factor in detecting these faults. (Short-time) Fourier, (continuous, discrete) wavelet, and extended Park vector transformations are among the methods for fault detection. One major deficiency of these methods is not being able to detect the severity of faults that carry low energy information, e.g. in ball bearing system failure, there is absolutely no way to detect the severity of fault using Fourier or wavelet transformations. In this paper, the authors have applied the Discrete Wavelet Transform (DWT) frequency-domain analysis to detect bearing faults in an induction motor. In other words, in discrete transform which the output signal is decomposed in several steps and frequency resolution increases considerably, the frequency-band analysis is performed and it will be verified that first of all, fault sidebands become more recognizable for detection in higher levels of decomposition, and secondly, the inner race bearing faults turn out easier in these levels; and all these matter because of eliminating the not-required high energy components in lower levels of decomposing.

• Environmental Engineering Research
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• v.21 no.1
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• pp.58-68
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• 2016

The study explored droughts using the Standardized Precipitation Index (SPI) in the northwestern region of Bangladesh, which is the drought prone area. In order to assess the trend and variability of monthly rainfall, as well as 3-month scale SPI, non-parametric Mann-Kendall (MK) tests and continuous wavelet transform were used respectively. The effect of climatic parameters on the drought in this region was also evaluated using SPI, with the Southern Oscilation Index (SOI) by means of the wavelet coherence technique, a relatively new and powerful tool for describing processes. The MK test showed no statistically significant monthly rainfall trends in the selected stations, whereas the seasonal MK test showed a declining rainfall trend in Bogra, Ishurdi, Rangpur and Sayedpur stations respectively. Sen's slope of six stations also provided a decreasing rainfall trend. The trend of the SPI, as well as Sen's slope indicated an increasing dryness trend in this area. Dominant periodicity of 3-month scale SPI at 8 to 16 months, 16 to 32 months, and 32 to 64 months were observed in the study area. The outcomes from this study contribute to hydrologists to establish strategies, priorities and proper use of water resources.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.107-127
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• 2022

Structural health monitoring (SHM) has been related to damage identification with either operational loads or other environmental loading playing a significant complimentary role in terms of structural safety. In this study, a non-parametric method of time frequency analysis on the measurement is used to address the time-frequency representation for modal parameter estimation and system damage identification of structure. The method employs the wavelet decomposition of dynamic data by using the modified complex Morlet wavelet with variable central frequency (MCMW+VCF). Through detail discussion on the selection of model parameter in wavelet analysis, the method is applied to study the dynamic response of both steel structure and reinforced concrete frame under white noise excitation as well as earthquake excitation from shaking table test. Application of the method to building earthquake response measurement is also examined. It is shown that by using the spectrogram generated from MCMW+VCF method, with suitable selected model parameter, one can clearly identify the time-varying modal frequency of the reinforced concrete structure under earthquake excitation. Discussions on the advantages and disadvantages of the method through field experiments are also presented.

• 한국도로학회:학술대회논문집
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• 2005.11a
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• pp.239-244
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• 2005

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.43-52
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• 2014

P-wave characteristic in the human electrocardiogram (ECG) is important in the diagnosis of atrial conduction pathology. In this paper, we measured an ECG signal from patient with cardiovascular disease using one lead ECG electrode system which is based on the wireless cardiac monitoring system. And we detected a P-wave in ECG signal using the complex-valued continuous wavelet transforms (CWT) according to two kinds of patch type electrodes such as an existing narrow patch type electrode and the improved wide patch type electrode presented in this paper. Also, we compared the characteristics in detecting the P-wave in terms of the magnitude and the width of P-waves. From the results of comparison we found that the width and the magnitude of P-wave detected using the wide patch type electrode is improved to be interpreted easier compared to those using the narrow patch type electrode. Furthermore, we have also proven that the complex-valued CWT can be used as a robust detector for P-wave in ECG signal analysis.

• Wind and Structures
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• v.38 no.4
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• pp.277-293
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• 2024

The recorded thunderstorm winds at a point contain tri-directional components. The probabilistic characteristics of such recorded winds in terms of instantaneous mean wind speed and direction, and the probability distribution and the time-frequency dependent crossed and non-crossed power spectral density functions for the high-frequency fluctuating wind components are unclear. In the present study, we analyze the recorded tri-directional thunderstorm wind components by separating the recorded winds in terms of low-frequency time-varying mean wind speed and high-frequency fluctuating wind components in the alongwind direction and two orthogonal crosswind directions. We determine the time-varying mean wind speed and direction defined by azimuth and elevation angles, and analyze the spectra of high-frequency wind components in three orthogonal directions using continuous wavelet transforms. Additionally, we evaluate the coherence between each pair of fluctuating winds. Based on the analysis results, we develop empirical spectral models and lagged coherence models for the tri-directional fluctuating wind components, and we indicate that the fluctuating wind components can be treated as Gaussian. We show how they can be used to generate time histories of the tri-directional thunderstorm winds.

• Nuclear Engineering and Technology
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• v.56 no.11
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• pp.4688-4697
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• 2024

Accurate nuclide identification in γ-spectrum analysis of low- and intermediate-level radioactive waste with high-purity germanium detectors necessitates initial forced fitting with a nuclide library, yet inaccuracies in library data may lead to misidentification and missing nuclides. To this end, background clipping strategies were hereby analyzed, and a novel deconvolution spectrum analysis method was proposed, which utilized continuous wavelet transform for peak searching and Gaussian first-order derivative quadratic convolution for calculating peak width. Furthermore, to effectively realize the nuclide identification and peak area calculation, a response filter function model was established through the peak shape calibration. By eliminating the need for nuclide library parameter settings prior to overlapping peak separation, the issue of inaccurate matching arising from reliance on the precision of the nuclide library was addressed. Moreover, spectrum analysis experiments were carried out on standard point sources and 200 L drums, and the results were compared and analyzed using GammaVision. Compared to the GammaVision results set by the accurate nuclide library, the area error of strong peaks decreased from 27.5 % to 4.82 %, while that of weak peaks witnessed a decline from 49.98 % to 27.5 %. Finally, the accuracy of the proposed method was verified using the Pakistan Nuclear Library.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.99-106
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• 2005

Instantaneous Frequency(IF) of Doppler signals is used to get the information of relative velocity and miss distance between a missile and the corresponding target. Though Short-Time Fourier Transform(STFT) is mainly used to estimate IF, it has many errors in wide band signals where frequency changes sharply. Because it has a fixed window in time and frequency axes. This paper deals with IF estimation of Doppler signal using a Continuous Wavelet Transform(CWT) which has adaptive window in time and frequency axes. The proposed method is able to estimate IF regardless of frequency changes because it has a narrow window in high frequency band and a wide window in low frequency band. The experimental results demonstrate that the proposed method outperforms STFT in estimating IF.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.513-518
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• 2008

The research of global-scale mass redistribution and it changed by Earth gravity filed variation observations, including Earth's oblateness $J_2$(also called low degree spherical harmonic coefficient $C_{20}$), is in continuous progress. Recently, the comparative analysis of geodetic observation SLR can be made by the development of GRACE and other time-variable gravity measurements. In this study, $C_{20}$ time series changes in the value of comparative analysis was got by GRACE monthly Gravity filed model (CSR RL04) for the period April 2002 to May 2008. And comparative analysis the harmonic coefficients of $C_{20}$ was obtained from SLR observations. Signal analysis for two time-series data was made by wavelet transform, CWT(continuous wavelet transform), XWT(cross wavelet transform) and WTC(wavelet coherence) methods. The results indicate that GRACE and SLR values for $C_{20}$ had both decreasing trend, as well as SLR data represent the annual frequencies, and GRACE was semiannual variations. In addition, the results of GRACE and SLR had a strong correlation with the XWT and WTC in an annual cycle.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.306-315
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• 2001

In noise reduction method from noisy speech for speech recognition in noisy environments, conventional spectral subtraction method has a disadvantage which distinction of noise and speech is difficult, and characteristic of noise can't be estimated accurately. Also, noise reduction method in the wavelet transform domain has a disadvantage which loss of signal is generated in the high frequency domain. In order to compensate theme disadvantage, this paper propose spectral subtraction method in continuous wavelet transform domain which speech and non- speech intervals is distinguished by standard deviation of wavelet coefficient, and signal is divided three scales at different scale. The proposed method extract accurately characteristic of noise in order to apply spectral subtraction method by end detection and band division. The proposed method shows better performance than noise reduction method using conventional spectral subtraction and wavelet transform from viewpoint signal to noise ratio and Itakura-Saito distance by experimental.