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Identification of failure mechanisms for CFRP-confined circular concrete-filled steel tubular columns through acoustic emission signals

  • Li, Dongsheng;Du, Fangzhu;Chen, Zhi;Wang, Yanlei
    • Smart Structures and Systems
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    • v.18 no.3
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    • pp.525-540
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    • 2016
  • The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

Arc Detection using Logistic Regression (로지스틱 회기를 이용한 아크 검출)

  • Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.566-574
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    • 2021
  • The arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet and statistical features have been used, arc detection performance is degraded due to diverse arc waveforms. On the contray, Deep neural network (DNN) direcly utilizes raw data without feature extraction, based on end-to-end learning. However, a disadvantage of the DNN is processing complexity, posing the difficulty of being migrated into a termnial device. To solve this, this paper proposes an arc detection method using a logistic regression that is one of simple machine learning methods.

Assessment of New High-resolution Regional Climatology in the East/Japan Sea

  • Lee, Jae-Ho;Chang, You-Soon
    • Journal of the Korean earth science society
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    • v.42 no.4
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    • pp.401-411
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    • 2021
  • This study provides comprehensive assessment results for the most recent high-resolution regional climatology in the East/Japan Sea by comparing with the various existing climatologies. This new high-resolution climatology is generated based on the Optimal Interpolation (OI) method with individual profiles from the World Ocean Database and gridded World Ocean Atlas provided by the National Centers for Environmental Information (NCEI). It was generated from the recent previous study which had a primary focus to solve the abnormal horizontal gradient problem appearing in the other high-resolution climatology version of NCEI. This study showed that this new OI field simulates well the meso-scale features including closed-curve temperature spatial distribution associated with eddy formation. Quantitative spatial variability was compared to the other four different climatologies and significant variability at 160 km was presented through a wavelet spectrum analysis. In addition, the general improvement of the new OI field except for warm bias in the coastal area was confirmed from the comparison with serial observation data provided by the National Fisheries Research and Development Institute's Korean Oceanic Data Center.

Voice Activity Detection Algorithm using Wavelet Band Entropy Ensemble Analysis in Car Noisy Environments (문서 편집 접근성 향상을 위한 음성 명령 기반 모바일 어플리케이션 개발)

  • Park, Joo Hyun;Park, Seah;Lee, Muneui;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.21 no.11
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    • pp.1342-1352
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    • 2018
  • Voice Command systems are important means of ensuring accessibility to digital devices for use in situations where both hands are not free or for people with disabilities. Interests in services using speech recognition technology have been increasing. In this study, we developed a mobile writing application using voice recognition and voice command technology which helps people create and edit documents easily. This application is characterized by the minimization of the touch on the screen and the writing of memo by voice. We have systematically designed a mode to distinguish voice writing and voice command so that the writing and execution system can be used simultaneously in one voice interface. It provides a shortcut function that can control the cursor by voice, which makes document editing as convenient as possible. This allows people to conveniently access writing applications by voice under both physical and environmental constraints.

The earth mover's distance and Bayesian linear discriminant analysis for epileptic seizure detection in scalp EEG

  • Yuan, Shasha;Liu, Jinxing;Shang, Junliang;Kong, Xiangzhen;Yuan, Qi;Ma, Zhen
    • Biomedical Engineering Letters
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    • v.8 no.4
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    • pp.373-382
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    • 2018
  • Since epileptic seizure is unpredictable and paroxysmal, an automatic system for seizure detecting could be of great significance and assistance to patients and medical staff. In this paper, a novel method is proposed for multichannel patient-specific seizure detection applying the earth mover's distance (EMD) in scalp EEG. Firstly, the wavelet decomposition is executed to the original EEGs with five scales, the scale 3, 4 and 5 are selected and transformed into histograms and afterwards the distances between histograms in pairs are computed applying the earth mover's distance as effective features. Then, the EMD features are sent to the classifier based on the Bayesian linear discriminant analysis (BLDA) for classification, and an efficient postprocessing procedure is applied to improve the detection system precision, finally. To evaluate the performance of the proposed method, the CHB-MIT scalp EEG database with 958 h EEG recordings from 23 epileptic patients is used and a relatively satisfactory detection rate is achieved with the average sensitivity of 95.65% and false detection rate of 0.68/h. The good performance of this algorithm indicates the potential application for seizure monitoring in clinical practice.

Improvement of inspection system for common crossings by track side monitoring and prognostics

  • Sysyn, Mykola;Nabochenko, Olga;Kovalchuk, Vitalii;Gruen, Dimitri;Pentsak, Andriy
    • Structural Monitoring and Maintenance
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    • v.6 no.3
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    • pp.219-235
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    • 2019
  • Scheduled inspections of common crossings are one of the main cost drivers of railway maintenance. Prognostics and health management (PHM) approach and modern monitoring means offer many possibilities in the optimization of inspections and maintenance. The present paper deals with data driven prognosis of the common crossing remaining useful life (RUL) that is based on an inertial monitoring system. The problem of scheduled inspections system for common crossings is outlined and analysed. The proposed analysis of inertial signals with the maximal overlap discrete wavelet packet transform (MODWPT) and Shannon entropy (SE) estimates enable to extract the spectral features. The relevant features for the acceleration components are selected with application of Lasso (Least absolute shrinkage and selection operator) regularization. The features are fused with time domain information about the longitudinal position of wheels impact and train velocities by multivariate regression. The fused structural health (SH) indicator has a significant correlation to the lifetime of crossing. The RUL prognosis is performed on the linear degradation stochastic model with recursive Bayesian update. Prognosis testing metrics show the promising results for common crossing inspection scheduling improvement.

Impact location on a stiffened composite panel using improved linear array

  • Zhong, Yongteng;Xiang, Jiawei
    • Smart Structures and Systems
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    • v.24 no.2
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    • pp.173-182
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    • 2019
  • Due to the degradation of beamforming properties at angles close to $0^{\circ}$ to $180^{\circ}$, linear array does not have a complete $180^{\circ}$ inspection range but a smaller one. This paper develops a improved sensor array with two additional sensors above and below the linear sensor array, and presents time difference and two dimensional multiple signal classification (2D-MUSIC) based impact localization for omni-directional localization on composite structures. Firstly, the arrival times of impact signal observed by two additional sensors are determined using the wavelet transform and compared, and the direction range of impact source can be decided in general, $0^{\circ}$ to $180^{\circ}$ or $180^{\circ}$ to $360^{\circ}$. And then, 2D-MUSIC based spatial spectrum formula using uniform linear array is applied for locate accurate position of impact source. When the arrival time of impact signal observed by two additional sensors is equal, the direction of impact source can be located at $0^{\circ}$ or $180^{\circ}$ by comparing the first and last sensor of linear array. And then the distance is estimated by time difference algorithm. To verify the proposed approach, it is applied to a quasi-isotropic epoxy laminate plate and a stiffened composite panel. The results are in good agreement with the actual impact occurring position.

Determination of Shear Wave Velocity Profile Model Considering Uncertainty Caused by Spatial Variation of Material Property in Rockfill Zone of Fill Dam (물성치 변동성에 의한 불확실성이 고려된 국내 필댐 사력부를 위한 전단파 속도 주상도 모델)

  • Park, Hyung-Choon
    • Journal of the Korean Geotechnical Society
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    • v.35 no.2
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    • pp.29-36
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    • 2019
  • There always exist the spatial variations of material properties such as a shear wave velocity in a dam and between same type dams. These uncertainties cause those in evaluation of a shear wave velocity profile of a dam and should be considered in determining the shear wave velocity profile for a rockfill zone of a fill dam. In this paper, these uncertainties of a shear wave velocity in the rockfill zone of the fill dam in Korea are evaluated. And the shear wave velocity profile model considering these uncertainties in rockfillzone is proposed using the method based on Harmonic wavelet transform. The proposed shear wave velocity profile model is compared with Sawada-Takahashi model widely used for evaluation of a shear wave velocity profile of a rockfill zone of fill dams.

Development of diagnosis index for tick/click and tone noise of blower motor using vibration signals (진동 신호를 이용한 블로워 모터 틱/클릭과 톤 소음의 진단 지수 개발)

  • Lee, Songjune;Cheong, Cheolung;Lee, In-Hyuk
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.3
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    • pp.363-369
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    • 2019
  • Various studies have been conducted for the diagnosis of noise condition of complex rotary machines. In this study, diagnosis index using vibration signal is developed for the efficient and objective assessment of noise condition of a blower motor. The noise most commonly caused by the abnormal blower motor are Tick/Click noise and Tone noise. According to cause and noise characteristics, time-frequency analysis is used to diagnose Tick/Click noise, and smoothing in frequency domain is used to diagnose tone noise condition. The noise condition of the blower motors were diagnosed using the developed index and these results are compared with the diagnostic results by the experts. As a result, the agreement rate was about 95 %.

Cross-Correlation of Oscillations in A Fragmented Sunspot

  • Lee, Kyeore;Chae, Jongchul
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.2
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    • pp.45.3-46
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    • 2018
  • Oscillations in a sunspot are easily detected through the Doppler velocity observation. Although the sunspot oscillations look erratic, the wavelet analysis show that they consist of successive wave packets which have strong power near three or five minutes. Previous studies found that 3-min oscillation at the chromosphere is a visual pattern of upward propagating acoustic waves along the magnetic field lines. Resent multi-height observations help this like vertical study, however, we also focus on horizontal facet to extend three dimensional understand of sunspot waves. So, we investigate a fragmented sunspot expected to have complex wave profiles according to the positions in the sunspot observed by the Fast Imaging Solar Spectrograph. We choose 4 points at different umbral cores as sampling positions to determine coherence of oscillations. The sets of cross-correlation with three and five minutes bandpass filters during a single wave packet reveal interesting results. Na I line show weak correlations with some lags, but Fe I and Ni I have strong correlations with no phase difference over the sunspots. It is more remarkable at Ni I line with 3-min bandpass that all sets of cross-correlation look like the autocorrelation. We can interpret this as sunspot oscillations occur spontaneously over a sunspot at photosphere but not at chromosphere. It implies a larger or deeper origin of 3-min sunspot oscillation.

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