• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.714-717
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• 1996

This paper presents a fault detection and diagnosis methodologies based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. At the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model(WSM) is used to generate those candidates. The weight is determined from dynamic simulation. Using WSMs, the methodology can generate the cause candidates and rank them according to the probability. Secondly, the fault propagation trends identified from the partial or complete sequence of measurements are compared to the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies and showed satisfactory diagnostic resolution.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.67-75
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• 2000

virtual computer numerical control(VCNC) arises from the concept that one can experience pseudo-real machining with a computer-numerically-controlled(CNC) machine before actually cutting an object. To achieve accurate VCNC, it is important to determine abnormal behavior, such as chatter, before cutting. Detecting chatter requires an understanding of the dynamic cutting force model. In general, the cutting process is a closed loop system the consists of structural and cutting dynamic. Machining instability, namely chatter, results from the interaction between these two dynamics. Several previous reports have predicted stability for a single path, using a simple cutting force model without run out and penetration effects. This study considers both tool run out and penetration effects, using experimental modal analysis, to obtain predictions that are more accurate. The machining stability during a corner cut, which is a typical transient cut, was assessed from an evaluation of the cutting configurations at the corner.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1542-1547
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• 2003

Air entrainment can become a significant problem in a web handling process. The development of air film between a web and an idle roller can cause a reduction of traction and traction coefficient, by which a slip is occurrred. Computational and experimental study was carried out to describe the slippage of an idle roller for given operating conditions, tension and web velocity. An extended mathematical model to find out a slip condition was developed by using the models of air film height, dynamic traction coefficient, and torque balance of a rotational roller. And by using the extended model, a mechanism to define the slippage between the roller and the moving web was suggested. The results of simulation and experiment showed that the extended dynamic model could properly characterize the rotational motion of the idle roller by considering dynamic traction coefficient. By examining the rotational motion of the idle roller with web dynamics(speed), the mechanism to define al slip condition between the roller and the web was found to be effective.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.204-210
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• 1998

This paper discusses an on-line fuzzy dynamic model(FDM) identification of nonlinear processes for the design of fuzzy model based fault detection and isolation(FDI). The dynamic behavior of a nonlinear process is represented by a fuzzy aggregation of a set of local linear models. The identification is divided into two procedures. The first is the off-line identification of membership function. The second is the on-line identification of the local linear models. Then, we propose a residual generation scheme based on the parameters of local linear models and show that the scheme can be used for the design of FDI

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.87.2-87.2
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• 2010

The steady and dynamic process model for an internal reforming molten carbonate fuel cell power plant is discussed in this paper. The dominant thermal and chemical dynamic processes are modeled for the stack module and balance-of-plant, including cathode gas preparation, heat recovery, heat loss (Each heat loss amount for the stack and MBOP is obtained from real plant data) and fuel processing. Based on dynamic model and control demand, PID controllers are designed in the whole system. By applying these controllers we can obtain temperature balance of stack and control system depending on changing steam to carbon ratio, air feed amount, and transient condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.442-448
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• 2000

The conventional control of dynamic systems needs accurate mathematical modeling of control systems. But the modeling of dynamic systems require very complex computation process due to complex state equation and many control parameters. Accordingly this paper proposes a state space identification model of the dynamic system using neural networks. The Gauss-Newton method is used to train the proposed neural network and the effectiveness of proposed method is verified through the computer simulation of the Seesaw system identification problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.643-647
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• 1996

The dynamic behavior of hydrostatic table is represented as the theoretical model, 1-dof, 2-dof rigid body spring-damper system, and finite element model. By the experimental and theoretical methods, the validity of these models and some other dynamic behaviors, such as the effects of unbalanced load and three dimensional motion, are investigated. To make easier to consider the dynamic behavior of hydrostatic table in design process, the stiffness and damping coefficients are calculated using the simple approximation method delived from the mass flow continuity condition, and compared with experimental results.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.161-166
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• 2006

This paper presents shift characteristics of a dual clutch transmission(DCT). To obtain the shift force, dynamic models of the DCT are constructed by using MATLAB/Simulink and considering the rotational inertia of every component and the target pre-select time. Dynamic models of the shift and clutch actuators are derived based on the experimental results of the dynamic characteristics test. Based on the dynamic model of the DCT synchronizer, control actuator and vehicle model, a DCT vehicle performance simulator is developed. Using the simulator, the shift force and speed of the relevant shafts are obtained. In addition, the torque and acceleration of actuators are calculated during the shift process by considering the engaging and disengaging dynamics of the two clutches. It is observed from the performance simulator that uninterrupted torque can be transmitted by proper control of the two clutches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1137-1140
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• 1993

A dynamic-structure system is one that has the flexibility to change the system configuration automatically so as to operate in an optimal manner. A conceptural model for a dynamic-structure system is presented in this paper. In this model, the interchangeable components of the overall system are grouped together. Their activity levels are evaluated by an intelligent preprocessor that is associated with the group. A knowledge-based task distribution system evaluates the activity levels and makes decisions as to how the components operating below capacity should be shared with workcells that have similar components that are overloaded. Associated decision making can be effected through fuzzy logic and particularly the compositional rule of inference. A simulation example is given to illustrate the application of dynamic structuring.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.