• Title/Summary/Keyword: Loss Estimation

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The Maximum Efficiency Driving in IPMSM by Precise Estimation of Current Phase Angle

  • Cho, Gyu-Won;Kim, Cheol-Min;Kim, Gyu-Tak
    • Journal of Electrical Engineering and Technology
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    • v.8 no.5
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    • pp.1221-1226
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    • 2013
  • In this paper, the equivalent circuit for the efficiency calculation by precise estimation of the linkage flux, inductance and iron loss resistance was calculated accurately. In addition, the driving characteristics according to the current phase angle are analyzed and the maximum efficiency point is calculated. And then, analyzed and experimental values of the efficiency were compared. So, causes of error were expected to be vibration and noise by harmonic distortion of the voltage and current, and mechanical loss of dynamometer. In addition, the driving characteristics according to the current phase angle are analyzed and the maximum efficiency point is calculated.

Supplementary analyses of economic X over bar chart model

  • Jeon, Tae-Bo
    • Korean Management Science Review
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    • v.12 no.1
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    • pp.111-124
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    • 1995
  • With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

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Estimating Fuzzy Regression with Crisp Input-Output Using Quadratic Loss Support Vector Machine

  • Hwang, Chang-Ha;Hong, Dug-Hun;Lee, Sang-Bock
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.10a
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    • pp.53-59
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    • 2004
  • Support vector machine(SVM) approach to regression can be found in information science literature. SVM implements the regularization technique which has been introduced as a way of controlling the smoothness properties of regression function. In this paper, we propose a new estimation method based on quadratic loss SVM for a linear fuzzy regression model of Tanaka's, and furthermore propose a estimation method for nonlinear fuzzy regression. This approach is a very attractive approach to evaluate nonlinear fuzzy model with crisp input and output data.

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New Approach for Improving Loss-free Handover Performance in DVB-H Networks (휴대방송 시스템(DVB-H)에서의 효과적인 핸드오버 기법 연구)

  • Cho, Jae-Soo;Park, Hung-Kun;Lim, Jong-Su;Lee, Hyun
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.87-89
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    • 2006
  • A handover for DVB-H(Digital Video Broadcasting for Handheld) is the action of switching a receiver from receiving one signal to receiving another, when moving between the border of their coverage areas. This paper proposes new approaches for improving loss-free handover performance in the DVB-H networks. The proposed handover schemes are targeted to two different DVB-H receivers: One is for the receivers equipped with GPS devices. The other is for ones without GPS support. The first handover approach modifies the cell description table(CDT) proposed in the literature[1]. The second proposes a novel handover region estimation technique based on a new handover map table(HMT). This new handover approach estimates a predefined hand over region described in the HMT using measured RSSIs signal patterns. The estimation success rate is simulated and the benefits of the proposed method are discussed considering time and power consumption.

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Experimental Methods for the Measurement of Damping Loss Factors (내부손실계수 측정을 위한 실험 방법)

  • 김관주;최승권
    • Journal of KSNVE
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    • v.9 no.6
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    • pp.1187-1192
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    • 1999
  • The purpose of this study is to determine the most appropriate experimental method of the measurement of "damping loss factors" (DLF) for the statistical energy analysis(SEA) calculation. The successful prediction of vibration levels from the structure is critically dependent on the accurate estimation of DLF's not only in conventional vibration analysis but especially in SEA. Unforunately, calculation of accurate DLF is not an easy matter. So experimental methods are made use of for the DLF values. Three kinds of experimental methods for estimating DLF, i.e. decay rate method, half-power bandwidth method and power balance method, are presented and tests are carried out for the plate and the cylindrical shell examples. Pro and con of each methods is reviewed. Finally, calculated DLF values are used for vibration level estimation using commercial SEA software and compared with measured vibration data.tion data.

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Nonparametric Bayesian estimation on the exponentiated inverse Weibull distribution with record values

  • Seo, Jung In;Kim, Yongku
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.3
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    • pp.611-622
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    • 2014
  • The inverse Weibull distribution (IWD) is the complementary Weibull distribution and plays an important role in many application areas. In Bayesian analysis, Soland's method can be considered to avoid computational complexities. One limitation of this approach is that parameters of interest are restricted to a finite number of values. This paper introduce nonparametric Bayesian estimator in the context of record statistics values from the exponentiated inverse Weibull distribution (EIWD). In stead of Soland's conjugate piror, stick-breaking prior is considered and the corresponding Bayesian estimators under the squared error loss function (quadratic loss) and LINEX loss function are obtained and compared with other estimators. The results may be of interest especially when only record values are stored.

The Estimation Method Comparison of Iron Loss Coefficients through the Iron Loss Calculation

  • Kim, Yong-Tae;Cho, Gyu-Won;Kim, Gyu-Tak
    • Journal of Electrical Engineering and Technology
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    • v.8 no.6
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    • pp.1409-1414
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    • 2013
  • A new calculation method for iron loss coefficients is proposed by using the Steinmetz equation from Epstein data. The hysteresis loss must have linear characteristic according to the frequency. However, the existing iron loss coefficients are defined by formula of frequency. In this case, the hysteresis loss has non-linear characteristics by frequency. So, in this paper, the iron loss coefficients were defined by a function of the magnetic flux density, and the iron loss calculation is applied for Interior Permanent Magnet Synchronous Motor(IPMSM) of 600(W) and 200(W). The iron loss calculation results and the experimental results are compared according to the various materials.

The Study of the Stray Load Loss and Mechanical Loss of Three Phase Induction Motor considering Experimental Results

  • Kim, Dong-Jun;Choi, Jae-Hak;Chun, Yon-Do;Koo, Dae-Hyun;Han, Pil-Wan
    • Journal of Electrical Engineering and Technology
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    • v.9 no.1
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    • pp.121-126
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    • 2014
  • The accurate determination of induction motor efficiency depends on the estimation of the five losses of stator and rotor copper loss, iron loss, mechanical loss and stray load loss. As the mechanical and stray load losses are not calculated by electro-magnetic analysis, the values of these two losses are very important in induction motor design. In this paper, the values of mechanical loss and stray load loss are proposed through investigating testing data from commercial products of three phase induction motors under 37kW. If the values of this paper are applied to motor design, the accuracy of design and analysis can be improved. The losses of motors are obtained by using load and no-load test results following IEC 60034-2-1 standard.

Estimation of Soil Loss by Land Use in the Geum River Basin using RUSLE Model (RUSLE 모델을 이용한 금강 유역의 토지 이용별 토사유출량 추정)

  • Park, Jisang;Kim, Geonha
    • Journal of Korean Society on Water Environment
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    • v.22 no.4
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    • pp.619-625
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    • 2006
  • Amount of soil loss is important information for the proper water quality management, In this research, annual average soil loss of the Geum River basin was estimated using RUSLE (Revised Universal Soil Loss Equation) and GIS (Geographic Information System). Input data were manipulated using ArcGIS ver. 8.3. From crop field which constitute 8.2% of the Geum River Basin, annual average soil loss was estimated as 53.6 ton/ha/year. From the rice paddy field which constitutes 20% of the Geum River Basin, soil loss was estimated as 33.5 ton/ha/year, In comparison, forestry area which constitutes 61.8% of the basin discharged 2.8 ton/ha/year, It could be known from this research that appropriate measures should be implemented to prevent excessive soil loss from the agricultural areas.

An Estimation of Head Loss Coefficients at Continuous Circular Manhole (연속 맨홀에서의 손실계수 산정)

  • Yoon, Young-Noh;Kim, Jung-Soo;Han, Chyung-Such;Yoon, Sei-Eui
    • 한국방재학회:학술대회논문집
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    • 2008.02a
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    • pp.731-734
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    • 2008
  • Urban sewer systems are designed to operate in open-channel flow regime and energy loss at circular manholes are usually not significant. However, the energy loss at manholes, often exceeding the friction loss of pipes under surcharge flow, is considered as one of the major causes of inundation in urban area. Therefore, it is necessary to analyze the head loss associated with manholes, especially in surcharge flow. Hydraulic experimental apparatus with two circular manholes was installed for this study. The range of the experimental discharges were from $1.0\ell/sec$ to $4.4\ell/sec$. Head loss coefficient was maximum because of strong oscillation of water surface when the range of manhole depth ratios$(h_m/D_{in})$ were from 1,2 to 1.25. The average head loss coefficients for upstream manhole and downstream manhole were 0.58 and 0.23 respectively. Head loss at upstream manhole is nearly 2.5 times more than one at downstream manhole.

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