• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.110-113
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• 2002

This paper propose a method for the temperature control using cool-plate in the track equipment. The employed control algorithm is PID control algorithm. The control gains are found using relay auto-tuning algorithm. After that the gains are adjusted manually in trial and error. The control hardware circuit is designed and implemented in the lab. The controlled temperature reached the desired value Within $\pm0.05^{\circ}C$ accuracy.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.6
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• pp.358-363
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• 2004

Due to the weather sensitivity of the power load, it is difficult to forecast accurately the peak power load of summer season. We improve the accuracy of the load forecasting considering weather condition. We introduced the sensitivity of temperature and proposed an improved forecasting algorithm. The proposed algorithm shows that the error of the load forecasting is 1.5%.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.510-512
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• 1997

Measurement errors in a temperature measurement system are mainly due to the consisting elements' accuracies and the circuit parameters' changes following the environment variations such as temperature. Further, system's non-linearity makes the measurement accuracy worse, and accordingly a linearization method should be considered to avoid this worsening. In this study, an error-correction method and a linearization method are proposed and a system utilizing these methods is realized.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.299-309
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• 2022

Recently, The sea water temperature around Korean Peninsula is steadily increasing. Water temperature changes not only affect the fishing ecosystem, but also are closely related to military operations in the sea. The purpose of this study is to suggest which model is more suitable for the field of water temperature prediction by attempting short-term water temperature prediction through various prediction models based on deep learning technology. The data used for prediction are water temperature data from the East Sea (Goseong, Yangyang, Gangneung, and Yeongdeok) from 2016 to 2020, which were observed through marine observation by the National Fisheries Research Institute. In addition, we use Long Short-Term Memory (LSTM), Bidirectional LSTM, and Gated Recurrent Unit (GRU) techniques that show excellent performance in predicting time series data as models for prediction. While the previous study used only LSTM, in this study, the prediction accuracy of each technique and the performance time were compared by applying various techniques in addition to LSTM. As a result of the study, it was confirmed that Bidirectional LSTM and GRU techniques had the least error between actual and predicted values at all observation points based on 1 hour prediction, and GRU was the fastest in learning time. Through this, it was confirmed that a method using Bidirectional LSTM was required for water temperature prediction to improve accuracy while reducing prediction errors. In areas that require real-time prediction in addition to accuracy, such as anti-submarine operations, it is judged that the method of using the GRU technique will be more appropriate.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.205-211
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• 2013

Recently, the needs of system performances such as working speed and processing accuracy in machine tools have been increased. Especially, the working speed increment generates harmful heat at both moving part of the machine tools and handicrafts. The heat is a main drawback to progress accuracy of the processing. Hence, a oil cooler to control temperature is inevitable for the machine tools. In general, two representative control schemes, hot-gas bypass and variable speed control of a compressor, have been adopted in the oil cooler system. This paper deals with design and implementation method of fuzzy controller for obtaining precise temperature characteristic of HB oil cooler system in machine tools. The opening angle of an electronic expansion valve are controlled to keep reference value and room temperature of temperature at oil outlet. Especially, the fuzzy controller is added to suppress temperature fluctuation under abrupt disturbances. Through some experiments, the suggested method can control the target temperature within steady state error of ${\pm}0.22^{\circ}C$.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.335-340
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• 2004

KS and ISO have proposed several evaluation methods of conventional machine tools. Even though the accuracy of the tools can be evaluated with those methods, there are still no proper evaluation methods of high speed machining. Because it is hard to evaluate characteristics of high speed machining such as decrease of cutting temperature, cutting force, and reduced machining time. Therefore, new evaluation method for high speed machine should be developed. In this paper, several shapes of model have been proposed to evaluate cutting accuracy of high speed machine.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.94-99
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• 2002

KS and ISO have proposed several evaluation methods of conventional machine tools. Even though the accuracy of the tools can be evaluated with these methods, there are still no proper evaluation methods of high speed machining. Because it is hard to evaluate characteristics of high speed machining such as decrease of cutting temperature, cutting force, and reduced machining time. Therefore, new evaluation method for high speed machine should be developed. In this paper, several shapes of model have been proposed to evaluate cutting accuracy of high speed machine.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.399-404
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• 2002

Improvement of measuring accuracy is an essential part of quality control manufacturing process. The OMM is less than the CMM in measure accuracy but the OMM system is more efficient, easier to use than other measurement system. About 40~70% of the machine tool errors are induced by the thermal errors. Therefore, a key requirement for improving the measuring accuracy is to reduce the geometric and thermal errors. Thermal errors are measured by a ball bar system and predicted by the thermal error modeling. Furthermore, using the pre-defined thermal error map approach compensates the geometric accuracy of the OMM. Appropriate experiments are performed using ball-bar system, temperature measuring devices and touch-type probe. Compensated results are compared with those obtained using CMM to verify the proposed methods.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.6
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• pp.138-145
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• 2007

Among various rapid prototyping processes, stereo-lithography process which can manufacture transparent prototype is known to be the greatest in the form & dimensional accuracy and surface roughness. In this paper, bench mark tests of 4 stereo-lithography-type rapid prototyping apparatus were carried out using transparent materials. The test includes measurement of mechanical properties, form accuracy, building speed and manufacturing cost. It was observed that ViperPRO of 3D systems is advantageous in the mechanical properties and building speed, RM600011 of CMET in sub-milli scale form accuracy and manufacturing cost, and relatively economical Eden500V of Objet is great in tensile strength at room temperature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1700-1705
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• 2009

In general, short term load forecasting is based on the periodical load pattern during a day or a week. Therefore, the conventional methods do not expose stable performance to every day during a year. Especially for anomalous weather conditions such as typhoons, the methods have a tendency to show the conspicuous accuracy deterioration. Furthermore, the tendency raises the reliability and stability problems of the conventional load forecast. In this study, a new load forecasting method is proposed in order to increase the accuracy of the forecast result in case of anomalous weather conditions such as typhoons. For irregular weather conditions, the sensitivity between temperature and daily load is used to improve the accuracy of the load forecast. The proposed method was tested with the actual load profiles during 14 years, which shows that the suggested scheme considerably improves the accuracy of the load forecast results.