• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.502-508
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• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.8
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• pp.43-49
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• 2009

This paper presents a routing mechanism to prolong the lifetime of error-prone wireless sensor networks. The proposed mechanism estimates the amount of energy consumption for communications and the expected residual energy in advance, which is based on the qualities of wireless links. Then, the proposed mechanism selects a path that is expected to have the most residual energy, and sends sensory data along the path. This mechanism reduces energy consumption caused by unnecessary retransmissions and distributes traffic evenly over the network owing to taking error rates into consideration, and extends energy depletion by selecting a path with the maximum of the minimal expected residual energy amounts. The experiment results show that the proposed mechanism prolongs network lifetime, compared to the existing methods.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.117-125
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• 2011

While human error happens repeatedly in the semiconductor industry in Korea, which has brought a tremendous loss from manpower, welfare etc., there are limitations to human error prevention activities. When a semiconductor company introduces new machines and facilities from Japan or Germany, the companies often do not consider human factors in the design. Also, semiconductor companies are so occupied with promoting increased productivity, their attention to human errors has been pushed aside. Negative aspects of technical exchange associated with safety management are one aspect of the industry's nature. A semiconductor company recently began acknowledging on the back of TQM(Total Quality Management) that human error has a decisive effect on the safety. There are a number of uncontrollable and hard to handle event sets because the nature of these events with a human error may often be threatened or very intensive. It is strongly required that systemic studies should be performed to grasp the whole picture of a current situation for hazard factors. This study aims to examine the human error approach through the case of human error prevention field activities in a semiconductor industry compared with the activities and experience in nuclear power plants.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.457-459
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• 2018

Solar power generation system is a energy generation technology that produces electricity from solar power, and it is growing fastest among renewable energy technologies. It is of utmost importance that the solar power system supply energy to the load stably. However, due to unstable energy production due to weather and weather conditions, accurate prediction of energy production is needed. In this paper, an Artificial Neural Network(ANN) that predicts solar energy using 15 kinds of meteorological data such as precipitation, long and short wave radiation averages and temperature is implemented and its performance is evaluated. The ANN is constructed by adjusting hidden parameters and parameters such as penalty for preventing overfitting. In order to verify the accuracy and validity of the prediction model, we use Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) as performance indices. The experimental results show that MAPE = 19.54 and MAE = 2155345.10776 when Hidden Layer $Sizes=^{\prime}16{\times}10^{\prime}$.

• Nuclear Engineering and Technology
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• v.22 no.2
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• pp.95-100
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• 1990

The exact expression for the 1151 force on a fuel assembly in a reactor core is derived in terms of calculable hydraulic parameters. The relation for the lift force. pressure drop, buoyancy force, viscous force. and fuel assembly weight is discussed. Based on the derived exact expression. error analysis is made for a simple expression applying COBRA IV-i to a typical PWR fuel assembly. The error analysis revealed that the error of the simple expression consists of four terms and the overall error depends on the flow rate change direction, and its magnitude is about 1%.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.265-273
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• 2007

This paper expands an analytical performance model of 802.11 to accurately estimate throughput and energy demand of 802.11-based wireless sensor network (WSN) when sensor nodes employ Reed-Solomon (RS) codes, one of block forward error correction (FEC) techniques. This model evaluates these two metrics as a function of the channel bit error rate (BER) and the RS symbol size. Since the basic recovery unit of RS codes is a symbol not a bit, the symbol size affects the WSN performance even if each packet carries the same amount of FEC check bits. The larger size is more effective to recover long-lasting error bursts although it increases the computational complexity of encoding and decoding RS codes. For applying the extended model to WSNs, this paper collects traffic traces from a WSN consisting of two TIP50CM sensor nodes and measures its energy consumption for processing RS codes. Based on traces, it approximates WSN channels with Gilbert models. The computational analyses confirm that the adoption of RS codes in 802.11 significantly improves its throughput and energy efficiency of WSNs with a high BER. They also predict that the choice of an appropriate RS symbol size causes a lot of difference in throughput and power waste over short-term durations while the symbol size rarely affects the long-term average of these metrics.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.4
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• pp.287-293
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• 2003

This study examined the temperature-dependent regression model of energy consumption based on various measuring period. The methodology employed was to construct temperature-dependent linear regression model of daily energy consumption from one day to three months data-sets and to compare the annual heating energy consumption predicted by these models with actual annual heating energy consumption. Heating energy consumption from a building in Daejon was examined experimentally. From the results, predicted value based on one day experimental data can have error over 100%. But predicted value based on one week experimental data showed error over 30%. And predicted value based on over three months experimental data provides accurate prediction within 6% but it will be required very expensive.

• Journal of the Korean Solar Energy Society
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• v.27 no.1
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• pp.1-9
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• 2007

This paper reveals both the operational situation and the cause of the error occurred in wind turbine generator system of Hangwon wind farm in Jeju island. The four wind turbines were selected for this work, and the monitored period was for six months. Wind resource in the wind farm was analyzed, and the estimated energy production was compared with the actual energy production. As a result, with a decrease of system error, the estimated energy production was in good agreement with the actual energy production. The errors occurring in components such as gearbox and hydraulic motor affected the Availability of the wind turbine. Also, poor external conditions such as a strong wind, lightning and gust caused a standstill of wind turbines.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2528-2530
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• 2000

In general, Diode makes a major role in electronic circuit. For example, switching of rectifier, cross current of switching rectifier, energy transfer of electronic element and reverse charge of capacitor, voltage insulation, energy feedback from load to power supply, and such as recovery of storaged energy. Generally, We regard power diode as ideal element, but it has a certain boundary actually, specially, We use diode for detecting circuit peak hold voltage signal. It has cut in voltage. It occurs error of measurement value namely. This error, below in region diode voltage drop (0.7v) measurement value is wholesome signal, Specially, We can not get precision data. Therefore, precision level is low between theoretical and measurement data because of error in actual circuit. Conclusionally, In this paper, We define the error concerning to the power diode characteristics which is used detecting of the minute signal, and recommend the method that minimize measurement error.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.657-662
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• 2019

The power consumption of wearable sensors and electrocardiogram regulators should be very low to extend the network lifetime and anticipated QoS( : Quality of Service) control such as error correction and authentication of data processed by WBAN( : Wireless Body Area Network) nodes is important. Therefore, QoS control is the most urgent concern to implement WBAN in health monitoring regulations. For optimal QoS control, we compare the energy efficiency and the average number of transmissions with IEEE 802.15.6 and the error correction method considering energy efficiency. The performance of the proposed error correction technique shows that the energy efficiency and the transmission rate are improved by adjusting the coding rate appropriately using the channel estimation.