• Journal of Korean Society of Transportation
• /
• v.22 no.7 s.78
• /
• pp.119-129
• /
• 2004

This paper is designed to report the results of development and validation procedures in relation to the Freeway Incident Management System (FIMS) prototype development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but the integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Korean freeway system. After through review and analysis of vehicle detection data, the pilot site led to the utilization of different technologies in relation to the specific needs and character of the implementation. This meant that the existing system was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The system validation specifications have identified two component data collection and analysis patterns which were outlined in the validation specifications; the on-line and off-line testing procedural frameworks. The off-line testing was achieved using asynchronous analysis, commonly in conjunction with simulation of device input data to take full advantage of the opportunity to test and calibrate the incident detection algorithms focused on APID, DES, DELOS and McMaster. The simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.6
• /
• pp.559-567
• /
• 2020

This paper proposes a noise cancelling algorithm to remove own-ship noise for a towed array sonar. Extra beamforming is performed using partial channels of the acoustic array to get a reference beam signal robust to the noise bearing. Frequency domain Adaptive Noise Cancelling (ANC) is applied based on Normalized Least Mean Square (NLMS) algorithm using the reference beam. The bearing of own-ship noise is estimated from the coherence between the reference beam and input beam signals. Own-ship noise level is calculated using a beampattern of the noise with estimated steering angle, which prevents loss of a target signal by determining whether to update a filter so that removed signal level does not exceed the estimated noise level. Simulation results show the proposed algorithm maintains its performance when the own-ship gets out off its bearing 40 % more than the conventional algorithm's limit and detects the target even when the frequency of the target signal is same with the frequency of the own-ship signal.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.533-538
• /
• 2004

This paper proposes a systematic method to develop short-term electrical load forecasting systems using neuro-fuzzy models. The proposed system predicts the electrical loads with the lead times of 1 hour, 24 hour, and 168 hour. To do so, the load forecasting system first builds an initial structure off-line for each hour of four day types and then stores the resultant initial structures in the initial structure bank. 96 initial structures are constructed for each prediction lead time. Whenever a prediction needs to be made, the proposed system initializes the neuro-fuzzy model with the appropriate initial structure stored and trains the initialized prediction modell. To improve the performance of the prediction system in terms of accuracy and reliability at the same time, the prediction model employs only two inputs. It makes possible to interpret the fuzzy rules to be learned. In order to demonstrate the viability of the proposed method, we develop a load forecasting system by using the real load data collected during 1996 and 1997 at KEPCO. Simulation results reveal that the prediction system developed in this paper can achieve a remarkable improvement on both accuracy and reliability

• The Transactions of the Korean Institute of Power Electronics
• /
• v.8 no.1
• /
• pp.80-88
• /
• 2003

In this paper, the new robust torsional vibration suppression control scheme is proposed for the two mass system. A reduced order state feedback controller where the motor speed and the observed torsional torque are fed back and the PI controller are proposed as the torsional vibration suppression controller. Using the estimated mechanical parameters by off-line RLS(Recursive Least Square) algorithms, the speed controller for torsional vibration suppression is designed and its gains are determined using the Kharitonov robust control theory. The Kharitonov robust control theory can obtain the robust stability with a specified stability margin and a damping limit and the good performance of vibration suppression although if the parameters are varied within some specified limit. The effectiveness and usefulness of the proposed schemes are verified with the simulation and the experimental results on the fully-digitalized 5.5kW two mass system.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.337-344
• /
• 2004

Most of the virtual space constructed sufficiently realistic need a lot of memory space to navigate smoothly. And this kind of virtual space also requires real-time responsibility for the navigation as well as realism. In the off-line virtual system, real-time responsibility can be resolved by using large scale if secondary memory. In the web-based online virtual system, on the other hand, real-time responsibility is highly related to the latency time of network data communication. This induces the necessity of the algorithm for fast data loading. In this paper, we propose and verify the validity of the two methodology for cell leading algorithm. According to the results of computer simulation, the algorithm using hexagonal type cell promotes the real-time responsibility over 30％ than that of the rectangular type.

• Journal of KIISE:Information Networking
• /
• v.29 no.3
• /
• pp.277-285
• /
• 2002

This paper proposes and analyzes an error control scheme for the transmission control based real-time communication, such as FDDI, TDMA, and wireless LAN, which delivers the message according to the round robin fashion after the off-line bandwidth allocation. Taking into account the time constraint of each message, the proposed error control scheme makes the receiver transmit the error report via asynchronous traffic while the sender resend the requested message via overallocated access time which is inevitably introduced by the bandwidth allocation procedure for hard real -time guarantee. The error control procedure does not interfere other real -time message transmissions. In addition, as each frame contains the size of the message it belongs, the receiver can recognize the end of completion of message transmission. This enables earlier error report to the receiver so that the sender can cope with more network errors. The analysis results along with simulation performed via SMPL show that the proposed scheme is able to enhance the deadline meet ratio of messages by overcoming the network errors. Using the proposed error control scheme, the hard real -time network can be built at cost lower than, but performance comparable to the expensive dual link network.

• Korean Chemical Engineering Research
• /
• v.46 no.6
• /
• pp.1043-1051
• /
• 2008

In polyolefin processes melt index (MI) is the most important controlled variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the $1^{st}$-order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. Using the model predictive control method based on the present dynamic MI estimation model, MI values are estimated and compared with those of MI setpoints. From the numerical simulation of the proposed control system, it was found that significant reduction of transition time and the amount of off-spec during grade changes were achieved.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.48 no.12
• /
• pp.1-7
• /
• 2011

In this work, an analytical models for the threshold voltage and flat band voltage have been suggested and proved using 3-dimensional device simulator. The method for device design guideline and its example in nanowire junctionless transistor and example of device design of was also presented. One can find that the suggested model for threshold voltage and flat band voltage agrees with 3-dimension simulation results. The threshold voltage and flat band voltage are decreased with the increase of nanowire radius, gate oxide thickness, and channel impurity doping concentration. When the work function of gate material and the ratio of ON and OFF current is given, the device design guide line for nanowire junctionless transistor has been proposed. It is known that the device with high impurity channel concentration can be fabricated with th decreased of nanowire radius and gate oxide thickness.

• Journal of Ocean Engineering and Technology
• /
• v.29 no.2
• /
• pp.143-153
• /
• 2015

This paper presents the results of an experimental study on the motion of an FPSO (Floating production storage and off-loading) and the characteristics of the mooring systejavascript:confirm_mark('abe', '1');m according to the turret position. Model tests of a turret-moored FPSO were carried out in the Ocean Engineering basin of KRISO. The FPSO was moored using an internal turret and catenary mooring. The models (1/60 scale) that were prepared included the FPSO, turret, and mooring lines. The experiments were conducted in irregular waves and combined environments, with waves, currents, and winds. A time-domain simulation was performed using OrcaFlex. The motion response and mooring line tension from the present calculations were compared with the results of experiments, and the agreement was fairly good. In addition, the results showed that the weathervaning stability was improved when the position of the turret was moved in the bow direction.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.16-21
• /
• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.