• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1596-1603
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• 2018

This paper presents the new design and validation process of the linear transverse flux machine of the stelzer machine for hybrid vehicle application. A linear transverse flux machine is a novel electric machine that has higher force density and power than conventional electric machine. The process concentrates on 2-dimensional and 3-dimensional analysis using equivalent magnetic circuit method considering leakage elements and it is verified by finite element analysis. Besides the force characteristics of all axis of each direction are analyzed. The study is considered by dividing the transverse flux electric excited type and the transverse flux permanent magnet excited type. Additionally three-dimensional analysis in this machine is accomplished due to asymmetric structure with another three axes. Finally, it suggests the new design and validation process of linear transverse flux machine for stelzer machine.

• 산업공학
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• 제24권1호
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• pp.8-14
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• 2011

Principal Component Analysis (PCA) reduces the dimensionality of the process by creating a new set of variables, Principal components (PCs), which attempt to reflect the true underlying process dimension. However, for highly nonlinear processes, this form of monitoring may not be efficient since the process dimensionality can't be represented by a small number of PCs. Examples include the process of semiconductors, pharmaceuticals and chemicals. Nonlinear correlated process variables can be reduced to a set of nonlinear principal components, through the application of Kernel Principal Component Analysis (KPCA). Support Vector Data Description (SVDD) which has roots in a supervised learning theory is a training algorithm based on structural risk minimization. Its control limit does not depend on the distribution, but adapts to the real data. So, in this paper proposes a non-linear process monitoring technique based on supervised learning methods and KPCA. Through simulated examples, it has been shown that the proposed monitoring chart is more effective than $T^2$ chart for nonlinear processes.

• 호남수학학술지
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• 제32권1호
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• pp.91-99
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• 2010

In this paper we introduce the concept of asymptotically almost negatively associated random variables in a Hilbert space and obtain the strong law of large numbers for a strictly stationary asymptotically almost negatively associated sequence of H-valued random variables with zero means and finite second moments. As an application we prove a strong law of large numbers for a linear process generated by asymptotically almost negatively random variables in a Hilbert space with this result.

• 호남수학학술지
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• 제36권3호
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• pp.679-688
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• 2014

The notion of asymptotically negative dependence for collection of random variables is generalized to a Hilbert space and the almost sure convergence for these H-valued random variables is obtained. The result is also applied to a linear process generated by H-valued asymptotically negatively dependent random variables.

• 연구논문집
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• 통권27호
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• pp.35-45
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• 1997

The dynamic design process for the articulated bogie of light rail vehicle(LRV) was studied to design a primary and secondary suspension elements. Suspension stiffness and damping is selected on the basis of the ride quality and suspension stroke trade-off. LRV was modeled as a 2 d.o.f linear system for the design of vertical suspension characteristics and a 4 d.o.f linear system for the design of lateral suspension characteristics. FRA's class-4-track irregularity was used for the exciting disturbance on track. The optimum value of primary and secondary suspension characteristics was determined using this design process.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.507-518
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• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제24권2호
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• pp.445-474
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• 2010

중학교 1학년 학생들의 일차방정식에 대한 풀이과정에 변화가 있는지를 알아보기 위하여 일차방정식을 학습한 후 1차 조사를 하고, 5개월이 지난 후에 2차 조사를 실시한 결과는 다음과 같다. 첫째, 1차 조사와 2차 조사 간의 정답 비율의 차이를 알아보기 위하여 McNemar검정을 실시한 결과, 유형A의 문항 x+4=9에서 $p=.035^a$, 문항 $x+\frac{1}{4}=\frac{2}{3}$에서 $p=.012^a$로 나타났으며, 유형B의 문항 x+3=8에서 $p=.012^a$, 문항 6(x+20)=20에서 $p=.035^a$으로 나타났다. 둘째, 1차 조사에서 문제 유형A와 유형B의 풀이과정을 올바르게 표현하지 못하였던 학생들 중에 2차 조사에서 올바르게 표현한 학생들이 있는 반면, 1차 조사에서 풀이과정을 올바르게 표현한 학생들 중에 2차 조사에서 오류를 범하는 학생들이 나타났다. 셋째, 모든 문항에 대하여 일차방식의 풀이과정을 올바르게 표현하는 학생들이 있는 반면, 몇 개 문항은 올바르게 표현하고 몇 개 문항은 그렇지 못한 학생들이 있었다. 결론적으로, 주어진 모든 문항에 대한 풀이 과정을 올바르게 표현하였더라도 또 다른 문항이 주어졌을 때 그 문항의 풀이과정에서 올바른 표현을 할 수 있다고 예견하기가 어렵다는 것이다. 논문에서 조사한 세 가지 유형(유형A, 유형B, 유형C)에 대한 학생들의 반응을 분석한 결과에 따르면, 이 세 가지 유형의 문제 풀이과정을 분석함으로써 어떤 학생이 일차방정식의 풀이과정을 올바르게 표현할 수 '있는지', '없는지'를 판단할 수 있다는 것이다.

• Korea-Australia Rheology Journal
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• 제21권2호
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• pp.135-141
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• 2009

Effect of activation energy and crystallization kinetics of polyethylenes (PEs) on the dynamics and stability has been investigated by changing rheological properties and crystallization rate in film casting process. The effect of changes of these properties has been shown using a typical example of short-chain branching (SCB) in linear polyethylenes. SCBs in linear polymers generally lead to the increase of the flow activation energy, and to the decrease of the crystallization rate, making polymer viscosity lower in the case of equivalent molecular weight. In general, the increment of the crystallinity of polymers under partially crystallized state helps to enhance the process stability by increasing tension, and lower fluid viscoelasticity possesses the stabilizing effect for linear polymers. It has been found that the fluid viscoelasticity plays a key role in the control of process stability than crystallization kinetics which critically depends on the cooling to stabilize the film casting process of short-chain branched polymers operated under the low aspect ratio condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1000-1003
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• 1996

Nonlinear unified predictive control(UPC) algorithm was applied to the temperature control of a batch polymerization reactor for polymethylmethacrylate(PMMA). Before the polymerization reaction is initiated, the parameters of the process model are determined by the recursive least squares(RLS) method. During the reaction, nonlinearities due to generation of heat of reaction and variation of heat transfer coefficients are predicted through the nonlinear model developed. These nonlinearities are added to the process output from the linear process model. And then, the predicted process output is used to calculate the control output sequence. The performance of nonlinear control algorithm was verified by simulation and compared with that of the linear unified predictive control algorithm. In the experiment of a batch PMMA polymerization, nonlinear unified predictive control was implemented to regulate the temperature of the reactor, and the validity of the nonlinear model was verified through the experimental results. The performance of the nonlinear controller turned out to be superior to that of the linear controller for tracking abrupt changes in setpoint.

• Journal of the Korean Statistical Society
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• 제31권4호
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• pp.483-490
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• 2002

A weak convergence is obtained for a linear process of the form (equation omitted) where {$\varepsilon$$_{t}$ } is a strictly stationary sequence of associated random variables with E$\varepsilon$$_{t}$ = 0 and E$\varepsilon$$^{^2}$$_{t}$ < $\infty$ and {a $_{j}$ } is a sequence of real numbers with (equation omitted). We also apply this idea to the case of linearly positive quadrant dependent sequence.