• 연구논문집
• /
• s.27
• /
• pp.153-166
• /
• 1997

In industry pneumatic control system has become a important means to obtain automation because of its simplicity, fast speed and low cost. However Due to of the compressibility of air and damping friction between moving parts, it is difficult to achieve high speed driving, accurate positioning and stopping without overshoot in one pneumatic control system. This paper describes the dynamic behaviors of pneumatic linear actuator. The results will be very useful in the prediction of actuated dynamics and for the manufacturers to improve the techniques in their redesign and get better performance. Also, the experimental data is very important for the dynamic simulation and theoretical analysis.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 1999.03b
• /
• pp.249-252
• /
• 1999

A numerical analysis was perfomed to predict flow curves and dynamic recrystallization behaviors of Al-5%Mg alloy on the basis of results of hot compression tests. The hot compression tests were carried out in the ranges of 350-50$0^{\circ}C$ and 5$\times${{{{ {10 }^{-3 } }}}}~3$\times${{{{ {10 }^{0 } }}}}/sec to obtain the Zener-Hollmon parameter. In the modelling equation the effects os strain hardening and dynamic recrystallization were taken into consideration. A model for predicting the evolution of microstructure in Al-5%Mg alloy during thermomechanical processing was developed in terms of dynamic recrystallization phenomena, The microstructure model was combined with finite element modeling(FEM) to predict microstructure development Model predictions showed good agreement with microstructures obtained in compression tests.

• Transactions of Materials Processing
• /
• v.17 no.2
• /
• pp.117-123
• /
• 2008

In this study, optimum processing condition of rolled AZ31 Mg alloy was investigated by utilizing processing map and constitutive equation considering microstructure evolution(dynamic recrystallization) occurring during hot-working. A series of mechanical tests were conducted at various temperatures and strain rates to construct a processing map and to formulate the recrystallization kinetics in terms of grain size. Dynamic recrystallization(DRX) was observed to occur at a domain of $250^{\circ}C$ and 1/s(maximum dissipation-efficiency region). The effect of DRX kinetics on microstructure evolution was implemented in a commercial FEM code followed by remapping of the state variables. The volume fraction and grain size of deformed part were predicted using a modified FEM code and were compared with those of actual hot forged part. A good agreement was observed between the experimented results and predicted ones.

• The Journal of the Korea Contents Association
• /
• v.8 no.10
• /
• pp.76-87
• /
• 2008

Prediction of travel time on road network is one of crucial research issue in dynamic route guidance system. A new approach based on Rule-Based classification is proposed for predicting travel time. This approach departs from many existing prediction models in that it explicitly consider traffic patterns during day time as well as week day. We can predict travel time accurately by considering both traffic condition of time range in a day and traffic patterns of vehicles in a week. We compare the proposed method with the existing prediction models like Link-based, Micro-T* and Switching model. It is also revealed that proposed method can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• Geomechanics and Engineering
• /
• v.13 no.5
• /
• pp.861-879
• /
• 2017

Coal and gas outburst is a serious dynamic disaster that occurs during coal mining and threatens the lives of coal miners. Currently, coal and gas outburst is commonly predicted using single indicator and its critical value. However, single indicator is unable to fully reflect all of the factors impacting outburst risk and has poor prediction accuracy. Therefore, a more accurate prediction method is necessary. In this work, we first analyzed on-site impacting factors and precursors of coal and gas outburst; then, we constructed a Fisher discriminant analysis (FDA) index system using the gas adsorption index of drilling cutting ${\Delta}h_2$, the drilling cutting weight S, the initial velocity of gas emission from borehole q, the thickness of soft coal h, and the maximum ratio of post-blasting gas emission peak to pre-blasting gas emission $B_{max}$; finally, we studied an FDA-based multiple indicators discriminant model of coal and gas outburst, and applied the discriminant model to predict coal and gas outburst. The results showed that the discriminant model has 100% prediction accuracy, even when some conventional indexes are lower than the warning criteria. The FDA method has a broad application prospects in coal and gas outburst prediction.

• The Journal of Information Technology and Database
• /
• v.6 no.1
• /
• pp.73-88
• /
• 1999

There have been a series of debates to determine whether it would be possible to forecast dynamic systems such as stock markets. Recently the introduction of chaos theory has allowed many researchers to bring back this issue. Their main concern was whether the behavior of stock markets is chaotic or not. These studies, however, present divergent opinions on this question, depending upon the method applied and the data used. And the issue of predictability based on the nonlinear, chaotic nature was not dealt extensively. This paper is to test the nonlinear nature of the Korea stock market and accordingly attempts to predict its behavior. The result indicates that our stock market represents a chaotic behavior. We also found out based on our simulation that executing buy/sell transactions based upon forecasts which were derived using the local approximation method outperforms the decision of holding without a buy/sell transaction.

• Proceedings of the KIEE Conference
• /
• 2005.11b
• /
• pp.35-38
• /
• 2005

This paper suggests the method that forecast Dynamic Line Rating (DLR). Thermal Overload Risk (TOR) of next time is forecasted based on current weather condition and DLR value by Monte Carlo Simulation (MCS). To model weather element of transmission line for MCS, we will propose the use of weather forecast system and statistical models that time series law is applied. Also, through case study, forecasted TOR probability confirmed can utilize by standard that decide DLR of next time. In short, proposed method may be used usefully to keep safety of transmission line and reliability of supply of electric Power by forecasting transmission capacity of next time.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.25 no.11
• /
• pp.731-738
• /
• 2015

This study proposed the method of the multi-crack detection using the sensitivity coefficient matrix which is calculated from the change of eigenvalues and eigenvectors before and after the crack. Each crack is modeled by a rotational springs. The method is applied to the cantilever beam with miulti-crack. The eigenvalues and eigenvectors are determined for different crack locations and depths. The prediction of multi-crack detection are in good agreement with the results of structural reanalysis.

• The Korean Journal of Applied Statistics
• /
• v.23 no.2
• /
• pp.249-261
• /
• 2010

Long-term forecasting of seasonal time series is critical in many applications such as planning business strategies and resolving possible problems of a business company. Unlike the traditional approach that depends solely on dynamic models, Li and Hinich (2002) introduced a combination of stochastic dynamic modeling with filter bank approach for forecasting seasonal patterns using highly coherent(High-C) waveforms. We modify the filter selection and forecasting procedure on wavelet domain to be more feasible and compare the resulting predictor with one that obtained from the wavelet variance estimation method. An improvement over other seasonal pattern extraction and forecasting methods based on such as wavelet scalogram, Holt-Winters, and seasonal autoregressive integrated moving average(SARIMA) is shown in terms of the prediction error. The performance of the proposed method is illustrated by a simulation study and an application to the real stock price data.

• Proceedings of the KIEE Conference
• /
• 1999.07a
• /
• pp.58-60
• /
• 1999

This paper presents dynamic performance prediction using Matlab / simulink after parameter estimation of synchronous reluctance motor considering iron loss. Test motor is 3 phase SynRM with the segmental rotor, rating power is 0.175KW. Experiment equipment is consists of testing motor, dynamometer, vector invertor dynamocontroller, and power analyser. The stator iron loss and rotor iron loss are modelled by additional windings on three-phase winding axis. These windings are transformed into d-q axis, and are represented as equivalent eddy current windings. P-Q circle diagram method and single phase standstill method are used to measure motor parameters considering iron loss.