• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.804-809
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• 1988

PRNM(Power Range Neutron Monitoring) of BWR (Boiling Water Reactor) is a system that processes signals from about two hundred LPRM (Local Power Range Monitor) sensors in the nuclear reactor and this system monitors the neutron flux level during the plant operating region. Development has been made by employing a special technique for multiplexing neutron sensor signals and the recent advanced microelectronics technology. It is applicable to the total plant digital control system for a nuclear power plant.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.127-135
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• 2022

With the advent of high technologies such as the 4th Industrial Revolution and artificial intelligence and big data, efforts are being made to solve urban problems and improve the quality of life by applying new technologies in the smart city field. In addition, as carbon neutrality has emerged as an important issue due to global warming, smart city energy platform technologies such as urban energy management, efficiency improvement, and carbon reduction are in the spotlight. In order to effectively manage urban energy, energy resource information such as electricity, water, gas, hot water, heating, etc. must be collected from the management system of various energy utilities and managed on the central platform. The centrally integrated data is delivered to external city management systems that require city energy information through an energy platform. This study developed a CIM profile for smart city energy monitoring required to provide energy data to external systems. Electric data model were designed using the CIM class of IEC 61970, and water, gas, and heat data model were designed in compliance with the UML-based design ideas of IEC 61970.

• Journal of the Korean Solar Energy Society
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• v.37 no.1
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• pp.81-90
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• 2017

We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%, the regression model using monitoring data for the specified interval of one year showed 0.22%. Root mean square error (RMSE) of 6 big data analysis models for power output prediction in May 2016 was analyzed 2.94% using a support vector regression model.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.505-524
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• 2010

Wireless structural monitoring systems consist of networks of wireless sensors installed to record the loading environment and corresponding response of large-scale civil structures. Wireless monitoring systems are desirable because they eliminate the need for costly and labor intensive installation of coaxial wiring in a structure. However, another advantageous characteristic of wireless sensors is their installation modularity. For example, wireless sensors can be easily and rapidly removed and reinstalled in new locations on a structure if the need arises. In this study, the reconfiguration of a rapid-to-deploy wireless structural monitoring system is proposed for monitoring short- and medium-span highway bridges. Narada wireless sensor nodes using power amplified radios are adopted to achieve long communication ranges. A network of twenty Narada wireless sensors is installed on the Yeondae Bridge (Korea) to measure the global response of the bridge to controlled truck loadings. To attain acceleration measurements in a large number of locations on the bridge, the wireless monitoring system is installed three times, with each installation concentrating sensors in one localized area of the bridge. Analysis of measurement data after installation of the three monitoring system configurations leads to reliable estimation of the bridge modal properties, including mode shapes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.532-539
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• 2007

Photovoltaic power generation system is one of new renewable energy sources. Such distributed power generation system has important issues for the system management ad operating after its installation. To solve the problem, remote monitoring and control systems can be employed. In this paper, LabVBEW based monitoring and control system is proposed for efficient management and operation of the photovoltaic power generation system. Interface method between monitoring part and DSP controller is given in detail. The proposed system is verified through experiments using a grid-connected photovoltaic power generation system.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.638-644
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• 2010

This paper presents ideas of service scenarios for home residents using electric power monitoring system per appliance, the implementation of the monitoring system, and analysis of acquired electric power usage pattern. By acquiring and analyzing electric power usage pattern, home residents can get information of power usage pattern of every legacy (non-Demand Response-ready) appliance. Further they can get pieces of recommendation how to reduce energy consumption, intelligent standby power blocking service, and alarming service to abnormality of appliances. In order to check the feasibility of the ideas, a system that can acquire electric power pattern per appliance is implemented, and electric power pattern of some appliances are stored to a database and it was analyzed to show if auto-identification of a type of a device is possible, which is a basic required function for the scenarios presented.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.83-89
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• 2005

Most domestic fossil power plants have exceeded 100,000 hours of operation with the severe operating condition. Among the critical components of fossil power plant, high temperature steam pipe systems have had a many problems and damage from unstable displacement behavior because of frequent start up and shut down. In order to prevent the serious damage and failure of the critical pipe system in fossil power plants, 3-dimensional displacement measurement system was developed for the on-line monitoring. Displacement measurement system was developed with a use of a LVDT type sensor and two rotary encoder type sensors. This system was installed and operated on the real power plant successfully.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• Tribology and Lubricants
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• v.36 no.6
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• pp.307-314
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• 2020

In this paper, studies on application cases of machine condition monitoring using oil sensors are reviewed. Owing to rapid industrial advancements, maintenance strategies play a crucial role in reducing the cost of downtime and improving system reliability. Consequently, machine condition monitoring plays an important role in maintaining operation stability and extending the period of usage for various machines. Machine condition monitoring through oil analysis is an effective method for assessing a machine's condition and providing early warnings regarding a machine's breakdown or failure. Among the three prevalent methods, the online analysis method is predominantly employed because this method incorporates oil sensors in real-time and has several advantages (such as prevention of human errors). Wear debris sensors are widely employed for implementing machine condition monitoring through oil sensors. Furthermore, various types of oil sensors are used in different machines and systems. Integrated oil sensors that can measure various oil attributes by incorporating a single sensor are becoming popular. By monitoring wear debris, machine condition monitoring using oil sensors is implemented for engines, automotive transmission, tanks, armored vehicles, and construction equipment. Additionally, such monitoring systems are incorporated in aircrafts such as passenger airplanes, fighter airplanes, and helicopters. Such monitoring systems are also employed in chemical plants and power plants for managing overall safety. Furthermore, widespread application of oil condition diagnosis requires the development of diagnostic programs.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.69-78
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• 2007

In recent years, embedded mobile systems have been expanding their application domains from embedded portable devices which only execute a specialized application such as MP3 player or digital camcoder to digital convergence devices which execute more complicated applications converged various functionalities such as video and audio play, digital dictionary, DMB, games, phone, etc. As it requires the increasing hardware performance such as more faster CPU and more larger RAM, display, disk size, it has brought about a corresponding increase in power consumption. However, coupled with relatively small gains in battery capacity over recent years, the importance of software architecture including intelligent power management has become paramount. In this paper, we have ported UbiFOSTM with energy saving techniques on the ARM9-based MBA2440 platform. For energy savings, we adapted the dynamic power management and the device power management schemes based on monitoring workload. Experimental results with some well-known applications show that proposed low power technique could save energy up to 24 %.