• 한국기계가공학회지
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• 제15권4호
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• pp.23-29
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• 2016

Rotary machine is major equipment in industry. The rotary machine is applied for a machine tool, ship, vehicle, power plant, and so on. But a spindle fault increase product's expense and decrease quality of a workpiece in machine tool. A turbine in power plant is directly connected to human safety. National crisis could be happened by stopping of rotary machine in nuclear plant. Therefore, it is very important to know rotary machine condition in industry field. This study mentioned fault diagnosis algorithm with statistical parameter and empirical mode decomposition. Vibration locations can be found by analyze kurtosis of data from triaxial axis. Support vector of data determine threshold using hyperplane with fault location. Empirical mode decomposition is used to find fault caused by intrinsic mode. This paper suggested algorithm to find direction and causes from generated fault.

• 대한의용생체공학회:의공학회지
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• 제18권4호
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• pp.413-420
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• 1997

In this paper, we analyzed the contraction patterns of active elbow muscles during isometric, concentric and eccentric contraction. The analysis parameters consist of frequency domain parameters (mean frequency, median frequency, peak frequency, peak power, skewness, kurtosis) and time domain paraseters (zero crossing, positive maxima, integrated EMG). The results of this study were as follows; The BR/BB of isometric contraction appeared to be Venter as the elbow joint was more extended. The BR /BB during concentric and eccentric contraction tended to increase with more extension of the elbow joint angle, but there was no significant difference between concentric and eccentric contraction. Further, the EMG power spectrum due to the type of contraction were different betwen eccentric and concentric contraction. According to the results, it was found that the activation pattern in elbow flexor muscles was different during three different muscle contraction pattern. Therefore, elbow flexor muscles should not be considered a single functioning unit. Especially, at the time domain analysis, IEMG is a dominant parameter for analysis of activation patterns, and the skewness kurtosis can be useful parameters in functional recognition for prosthesis control purpose.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 추계학술대회 논문집(제1권)
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• pp.175-180
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• 2006

본 연구는 제주도 서측 해역의 현지 파랑관측 자료를 기초로 해양파의 비선형 특성을 조사한 것으로서, 실제 해역에서의 Freak wave 예보의 토대를 마련하기 위한 기초 연구이다. 관측된 파랑자료의 비선형 특성을 조사하기 위해 파형의 상하 비대칭성, 전후비대칭성, 빈도 분포의 첨예도, 파랑 스펙트럼의 대역폭 파라미터 등을 추출하고 이를 자료를 유의파고, 최대파고 등의 파랑 특성치들과의 상관관계를 분석하였다.

• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.539-557
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• 1998

This article is concerned with the problem of estimating the mean of a one-parameter exponential family through sequential sampling in three stages under quadratic error loss. This more general framework differs from those considered by Hall (1981) and others. The differences are : (i) the estimator and the final stage sample size are dependent; and (ii) second order approximation of a continuously differentiable function of the final stage sample size permits evaluation of the asymptotic regret through higher order moments. In particular, the asymptotic regret can be expressed as a function of both the skewness $\rho$ and the kurtosis $\beta$ of the underlying distribution. The conditions on $\rho$ and $\beta$ for which negative regret is expected are discussed. Further results concerning the stopping variable N are also presented. We also supplement our theoretical findings wish simulation results to provide a feel for the triple sampling procedure presented in this study.

• 대한안전경영과학회지
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• 제13권1호
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• pp.195-202
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• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2000년도 하계학술대회 논문집
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• pp.585-591
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• 2000

The wavelet transform is the most recent technique for processing signals with time-varying spectra. In this paper, the wavelet transform is utilized to improved the assessment and multi-resolution analysis of acoustic emission signals generating in partial discharge. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals in case of applied voltage 20[kv]. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We applied FIR(Finite Impulse Response)digital filter algorithm in discrete to suppression for random noise. The white noise be included high frequency component denoised as decomposition of discrete wavelet transform level-3. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of acting(the early period, the last period) .

• 한국전기전자재료학회논문지
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• 제20권7호
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• pp.645-649
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• 2007

Partial discharge(PD) test for simulated insulation defects of used hydro generator stator winding was conducted to analyze the PD Parameters. Simulated insulation defects are classified by 5 types corona, slot, internal, multi and aging defect. Phase resolved partial discharge, statistical parameter (skewness, kurtosis), PD magnitude as a function of the test voltage(Q-V curve) and PD magnitude change under test voltage for 2 minutes are used as PD parameters. The analysis of PD parameters by 4 types are proved to be useful methods. In particular, PD parameter characteristics of aging defect could help to assess the aging condition of stator winding because aging defect has more weak insulation strength than other insulation defects : PD distribution is wide and flat, PD rises rapidly near $0^{\circ}\;and\;180^{\circ}$ and Q-V curve rises sharply and then gently drops.

• 소성∙가공
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• 제26권2호
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• pp.108-114
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• 2017

Titanium based implants are known to improve their osseointegration by controlling surface roughness from nanometers to micrometers. Implants continuously and/or repeatedly receive irregular loads in the human body, and require a deeper understanding of the tensile and fatigue properties that can determine the fracture characteristics of the materials. In this study, the plastic deformation behavior which depends on the surface geometry of the materials during tensile tests was analyzed using the finite element method. As a result, the tensile properties were greatly decreased with increasing the sharpness of the surface. On the other hand, the average roughness had no significant effect on tensile properties. This investigation shed a light on developing titanium implants with improved osseointegration by surface treatments.

• 한국정밀공학회지
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• 제28권1호
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• pp.56-62
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• 2011

Terrain recognition ability is crucial to the performance of legged robots in an outdoor environment. For instance, a robot will not easily walk and it will tumble or deviate from its path if there is no information on whether the walking surface is flat, rugged, tough, and slippery. In this study, the ground surface recognition ability of robots is discussed, and to enable walking robots to recognize the surface state and changes, a central moment method was used. The values of the sensor signals (load cell) of robots while walking were detected in the supported section and were analyzed according to signal variance, skewness, and kurtosis. Based on the results of such analysis, the surface state was detected and classified.

• 한국해양공학회지
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• 제26권2호
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• pp.8-13
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• 2012

This paper investigates the statistical properties of waves in the sea area of Uljin, which is located in the East Sea area of Korea. The wave data were measured using AWAC (Acoustic Wave and Current Meter), which was installed at a 16-m water depth from November 2010 to March 2011. The wave data acquisition rate, Hmax, monthly mean Hs, Tz, Tp, and wave direction are summarized. The distributions of Hs and Tz were analyzed using the Hs-Tz scatter diagrams. The measurement wave data were analyzed to investigate freak wave characteristics. By comparing the wave spectrum using the measurement wave data with the wave spectrum obtained by varying the JONSWAP wave spectrum, it was possible to approximate the wave spectrum shape at the Uljin Sea area.