• Smart Structures and Systems
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• 제15권3호
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.631-652
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• 2023

In the two-condition within-subject mediation design, pairs of variables such as mediator and outcome are observed under two treatment conditions. The main objective of the design is to investigate the indirect effects of the condition difference (sum) on the outcome difference (sum) through the mediator difference (sum) for comparison of two treatment conditions. The natural condition variables mean the original variables, while the rotated condition variables mean the difference and the sum of two natural variables. The outcome difference (sum) is expressed as a linear model regressed on two natural (rotated) mediators as a parallel two-mediator design in two condition approaches: the natural condition approach uses regressors as the natural condition variables, while the rotated condition approach uses regressors as the rotated condition variables. In each condition approach, the total indirect effect on the outcome difference (sum) can be expressed as the sum of two individual indirect effects: within- and cross-condition indirect effects. The total indirect effects on the outcome difference (sum) for both condition approaches are the same. The invariance of the total indirect effect makes it possible to analyze the nature of two pairs of individual indirect effects induced from the natural conditions and the rotated conditions. The two-condition within-subject design is extended to the addition of a between-subject moderator. Probing of the conditional indirect effects given the moderator values is implemented by plotting the bootstrap confidence intervals of indirect effects against the moderator values. The expected indirect effect with respect to the moderator is derived to provide the overall effect of moderator on the indirect effect. The model coefficients are estimated by the structural equation modeling approach and their statistical significance is tested using the bias-corrected bootstrap confidence intervals. All procedures are evaluated using function lavaan() of package {lavaan} in R.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.946-949
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• 2005

It is very a time-consuming and error-prone process to obtain the optimal injection condition, which can produce good injection molding products in some operational variation of facilities, from a seed injection condition. This study proposes a new approach to search the optimal injection molding condition using a neural network and a genetic algorithm. To estimate the defect type of unknown injection conditions, this study forces the neural network into learning iteratively from the injection molding conditions collected. Major two parameters of the injection molding condition - injection pressure and velocity are encoded in a binary value to apply to the genetic algorithm. The optimal injection condition is obtained through the selection, cross-over, and mutation process of the genetic algorithm. Finally, this study compares the optimal injection condition searched using the proposed approach. with the other ones obtained by heuristic algorithms and design of experiment technique. The comparison result shows the usability of the approach proposed.

• Tribology and Lubricants
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• 제36권6호
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• pp.307-314
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• 2020

In this paper, studies on application cases of machine condition monitoring using oil sensors are reviewed. Owing to rapid industrial advancements, maintenance strategies play a crucial role in reducing the cost of downtime and improving system reliability. Consequently, machine condition monitoring plays an important role in maintaining operation stability and extending the period of usage for various machines. Machine condition monitoring through oil analysis is an effective method for assessing a machine's condition and providing early warnings regarding a machine's breakdown or failure. Among the three prevalent methods, the online analysis method is predominantly employed because this method incorporates oil sensors in real-time and has several advantages (such as prevention of human errors). Wear debris sensors are widely employed for implementing machine condition monitoring through oil sensors. Furthermore, various types of oil sensors are used in different machines and systems. Integrated oil sensors that can measure various oil attributes by incorporating a single sensor are becoming popular. By monitoring wear debris, machine condition monitoring using oil sensors is implemented for engines, automotive transmission, tanks, armored vehicles, and construction equipment. Additionally, such monitoring systems are incorporated in aircrafts such as passenger airplanes, fighter airplanes, and helicopters. Such monitoring systems are also employed in chemical plants and power plants for managing overall safety. Furthermore, widespread application of oil condition diagnosis requires the development of diagnostic programs.

• 전기학회논문지
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• 제61권10호
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• pp.1508-1512
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• 2012

This paper presents a relaxed stability condition for continuous-time affine fuzzy system using fuzzy Lyapunov function. In the previous studies, stability conditions for the affine fuzzy system based on quadratic Lyapunov function have a conservativeness. The stability condition is considered by using the fuzzy Lyapunov function, which has membership functions in the traditional Lyapunov function. Based on Lyapunov-stability theory, the stability condition for affine fuzzy system is derived and represented to linear matrix inequalities(LMIs). And slack matrix is added to stability condition for the relaxed stability condition. Finally, simulation example is given to illustrate the merits of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.18-21
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• 2001

In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network me provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. In the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shoo's that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2004년도 춘계 학술대회지
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• pp.100-101
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• 2004

[ $\bigcirc$ ] In the growth simulation using genetic coefficients calculated with fooled data under various condition, WAGT was not higher and LAI, WLVG, WSO were higher, but WST was similar before grain-filling stage after the became lower because of higher translocation of carbohydrates than in the growth simulation using genetic coefficients calculated with data under high nitrogen applicated condition. $\bigcirc$ Genetic coefficients should be calculated with data showing potential in ORYZA2000, but under 180 kg and 240 kg N condition in 2003, plants were infected by panicle blast and also yield was not higher than under 120 kg N condition showing not potential condition and therefore not appropriate for genetic coefficients estimation compared with pooled data from various condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.1006-1013
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• 1988

We have shown how unstructured modeling was used to derive a general stability condition in Part 1. In Part 2, we focus on the particular dynamics (structures modeling) of the robot manipulator and environment. Using rigid body dynamics, the stability condition for the direct drive robots has been achieved in terms of the Jacobian and robot tracking controller. Combining the structured and unstructured modeling, a stability condition for a particular application can be obtained. This approach has been used to analyze compliant motion on the University of Minnesota robot using a feedforward torque controller. We have obtained a stability condition for this application. Through both simulation and experiment, the sufficiency of this condition has been demonstrated. For a sufficient stability condition, recall that if the condition is satisfied, then the stability is guaranteed; however, if the condition is violated, no conclusion can be made.

• 대한기계학회논문집B
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• 제33권3호
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• pp.164-169
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• 2009

The slip velocity and the temperature jumps for low-speed flow in microchannels are investigated using Langmuir slip boundary condition. This slip boundary condition is suggested to simulate micro flow. The current study analyzes Langmuir slip boundary condition theoretically and it analyzed numerically micro-Couette flow, micro-Poiseuille flow and grooved microchannel flow. First, to prove validity for Langmuir slip condition, an analytical solution for micro-Couette flow is derived from Navier-Stokes equations with Langmuir slip conditions and is compared with DSMC and an analytical solution with Maxwell slip boundary condition. Second, the numerical analysis is performed for micro-Poiseuille flow and grooved microchannel flow. The slip velocity and temperature distribution are compared with results of DSMC or Maxwell slip condition and those are shown in good agreement.

• 대한전기학회논문지
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• 제38권11호
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• pp.950-957
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• 1989

We have shown how unstructured modeling was used to derive a general stability condition in Part 1. In Part 2, we focus on the particular dynamics (structured modiling) of the robot manipulator and environment. Using rigid body dynamics, the stability condition for the direct drive robots has been achieved in terms of the Jacobian and robot tracking controller. Combining the structured and unstructured modeling, a stability condition for a particular application can be obtained. This approach has been used to analyze compliant motion on the University of Minnesota robot using a feedforward torque controller. We have obtained a stability condition for this application. Through both simulation and experiment, the sufficiency of this condition has been demonstrated. For a sufficient stability condition, recall that if the condition is satified, then the stability is guaranteed` however, if the condition is violated, no conclusion can be made.