• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.603-610
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• 2001

Industrial processes are normally operated by skilled humans who have the cumulative and logical information about the system. Fuzzy control has been investigated for many application. Intelligent control approaches based on fuzzy logic have a chance to include human thinking. This paper represents modeling approach based upon operators knowledge without mathematical model of the system and optimize the controller. The experimented system is constructed for sending a ball to the goal position using wind of two DC motors in the predefined path. A vision camera to mimic human eyes detects the ball position. The system used in this experiment could be hardly modeled by mathematical methods and ould not be easily controlled by conventional manners. The controller is designed based on the input-output data and experimental knowledge obtained by trials, and optimized under the predefined performance criterion. And this paper shows the data adaptation for changeable operating condition. When the system is driven in the abnormal condition with unconsidered noise, the new optimal operating parameters could be defined by adjusting membership functions. Thus, this technique could be applied in industrial fields.

• The KSFM Journal of Fluid Machinery
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• v.14 no.2
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• pp.17-24
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• 2011

Temperature gradient focusing (TGF) of analytes via Joule heating is achieved when electric field is applied along a microchannel of varying width. The effect of varying width of the microchannel for the focusing performance of the device was numerically studied. The governing equations were implemented into a quasi-1D numerical model along a microchannel. The validity of the numerical model was verified by a comparison between numerical and experimental results. The distributions of temperature, velocity, and concentration along a microchannel were predicted by the numerical results. The narrower middle width and wider outside width of the channel having the fixed length contribute to improve the focusing performance of the device. However, too narrow middle width of the channel generates a higher temperature which can cause the problems including sample denaturation and buffer solution boiling. Therefore, the channel geometry should be optimized to prevent these problems. The optimal widths of the microchannel for the improvement on TGF were proposed and this model can be easily applied to lab-on-a-chip (LOC) applications where focusing is required based on its simple design.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.26 no.6
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• pp.258-262
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• 2016

Foam reaction injection molding (FRIM) is a widely used process for manufacturing polyurethane foam with complex shapes. The modified theoretical model for polyurethane foam forming reaction during FRIM process was established in our previous work. In this study, using the modified model, parametric study for FRIM process was performed in order to optimize experimental conditions of FRIM process such as initial temperature of mold, thickness of mold, and injection amount of polymerizing mixture. In addition, we applied the modified model to real application of refrigerator cabinet to determine optimal manufacturing conditions for polyurethane FRIM process.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.199-203
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• 2018

Because of emission control of greenhouse gas, shipbuilders, especially those in Korea, are pushing forward to introduce eco-friendly ship-building technology utilizing LNG. However, Technical skills of domestic shipbuilders in manufacturing the cryogenic pump designed to supply LNG for vessels are so low that technical skills for design and manufacturing of core parts are in urgent need. Therefore, This study described about the Rotor as a core part of cryogenic submerged centrifugal pump for ship LNG supply system. We wish to utilize for the basic data to develop the technology for the Rotor as deducing the optimal outcome with the experimental and the analytical methods in material selection.

• 한국가시화정보학회:학술대회논문집
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• 2002.04a
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• pp.79-84
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• 2002

Most microfluidic devices such as heat sinks for cooling micro-chips, DNA chip, Lab-On-Chip, and micro pumps etc. have microchannels of various size. Therefore, the design of practical microfluidics demands detail information on flow structure inside the microchannels. However, detail velocity field measurements are rare and difficult to carry out. In addition, as the microfluidics expands, accurate understanding of microscale transport phenomena becomes very important. In this research, micro-PIV system was employed to measure the velocity fields of flow inside a micro-channel. We carried out PIV measurements for several microchannels with varying channels width, inlet and outlet shape, filters, CCD camera and ICCD camera, etc. For effective composition of micro-PIV system, first of all, it is essential to understand optics related with micro-imaging of particles and the particle dynamics encountered in micro-scale channel flows. In addition, it is necessary to find the optimal condition for given experimental environment and? micro-scale flow to be investigated. The problems encountered in measuring velocity field of micro-channel flows are discussed in this paper.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.71-84
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• 2006

Case-based reasoning (CBR) is a reasoning technique that reuses past cases to find a solution to the new problem. It often shows significant promise for improving effectiveness of complex and unstructured decision making. It has been applied to various problem-solving areas including manufacturing, finance and marketing for the reason. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still a challenging issue. Most of the previous studies on CBR have focused on the similarity function or optimization of case features and their weights. According to some of the prior research, however, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. In spite of the fact, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the novel approach to Korean stock market. Experimental results show that the GA-optimized k-NN approach outperforms other AI techniques for stock market prediction.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.83-91
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• 2006

At present, industry and researchers are looking for ways to reduce the use of lubricants because of ecological and economical reasons. Therefore, metal cutting is to move toward dry cutting or semi-dry cutting. One of the technologies is known as MQL(Minimum Quantity Lubrication) machining. This research presents an investigation into MQL machining with the objective of deriving the optimum cutting conditions for the turning process of SM4SC. To reach these goals several finish turning experiments were carried out, varying cutting speed, feed rate, oil quantity and so on, with MQL and flood coolant. The surface roughness and cutting force results of tests were measured and the effects of cutting conditions were analyzed by the method of Analysis of Variance(ANOVA). From the experimental results and ANOVA, this research proposed optimal cutting conditions to improve the machinability in MQL turning process.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.302-307
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• 2001

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller can be tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• The Korean Journal of Food And Nutrition
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• v.27 no.4
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• pp.706-715
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• 2014

The purpose of this study was to determine the optimal mixing ratio of Alaska Pollack (Theragra chalcogramma) and olive oil in the preparation of sausage. The experiment was designed according to the central composite design for estimating the response surface, which demonstrated 10 experimental points including 2 replicates for Alaska Pollack and olive oil. The physical, mechanical and sensory properties of test materials were measured. A canonical form and perturbation plot showed the influence of each ingredient on the final product mixture. Measurement results of the physical and mechanical properties showed a significant increase or decrease in the following properties: dough sweetness (p<0.05); sausage L (p<0.05), a (p<0.001), and b (p<0.01); hardness (p<0.01), chewiness (p<0.05), and gumminess (p<0.01). Also, the sensory measurements showed a significant improvement in color (p<0.05), flavor (p<0.01), taste (p<0.001), tenderness (p<0.05), chewiness (p<0.01), mositness (p<0.05), and overall quality (p<0.01). As a result, the optimum formulation by numerical and graphical methods was calculated as Alaska Pollack 35.74 g and olive oil 7 g.