• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.19-23
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• 2013

This research is about the Implementation of Remote Machine Health Monitoring System using Internet. This research will help users in the un-installed office to save a lot of cost and time from checking and managing machines' condition installed in the factory. We have made an experiment and developed the application program and the monitoring terminal which can monitor the machine's condition. This research will contribute to the development of internet and remote instrumentation engineering in the future. Finally the performance of the proposed system was evaluated through experiments, it showed the good performance and the possibility of commercialization.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.64-70
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results. it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.84-88
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results, it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.417-420
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• 2001

The monitoring system for maintaining on-site wastewater treatment plants(Biofilter) was developed. Proposed system applied PLC(Programmable Logic Controller) technique. In process of development, the research against the monitoring parameters which will be able to represent condition and operation of the plants was accomplished. These parameters are ORP(Oxidation-Reduction Potential), Water Level, Pump and Power on/off. Also, to measure, collect, transfer and display these parameters, DMU(Data Measurement Unit), MCU(Main Controller Unit) and Display Board were produced.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.4
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• pp.393-399
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• 2009

Historically, industrial condition monitoring has been performed by costly hard-wired sensors or infrequent checks by maintenance personnel equipped with hand held monitoring equipment. Self- powered wireless condition monitoring systems provides on-line monitoring of critical plant and machinery providing major operating cost benefits. A vibration energy harvester(VEH) is a device that converts kinetic energy occurred by machine vibration into useable electrical energy. Using VEHs to power wireless monitoring systems can yield significant benefits: increased reliability, lower life time costs and no battery disposal issues, etc. This paper proposes the novel prototype design and manufacturing of a VEH that can eliminate the effect by failed batteries.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1109-1115
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• 2008

In the ubiquitous health monitoring environments, it is quite important not only to evaluate the physiological health condition but also mental stress condition. In order to achieve this goal, a heart activity monitoring system utilizing a wearable bipolar electrode is devised and the heart rate variability(HRV) is extracted and interpreted in both frequency and time feature domains. Consequently, to evaluate the emotional stress condition of the subjects, a stress-induced experimental protocol was applied to healthy subjects and the time and frequency features of heart activity were analyzed in terms of the ratio of low frequency components v.s., high frequency components and the relevant the moving average distributions compromising the successive RR peaks intervals in the ambulatory ECG measurement system.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1119-1123
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• 2006

The flame image processing and analysis system has been investigated for the optimal pulverized coal firing of thermal power plant, especially for lower nitrogen oxide generation and more safe operation. We aimed at gaining the relationship between burner flame image information and emissions of nitrogen oxide and unburned carbon in furnace utilizing the flame image processing methods, by which we quantitatively determine the condition of combustion on the individual humors. Its feasibility test was undertaken with a pilot furnace for coal firing, through which the system was observed to be effective for the monitoring of the combustion condition of pulverized coal firing boilers.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1259-1267
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• 2008

One of the most important item for insuring the stability of ground in urban deep excavation site near by major structure such as subway is displacement control of earth retaining wall. The field monitoring system is classified by two types as manual system and automatic system. The application case of latter type of field monitoring is increased because real time measurement is possible in automatic system and that is correspondent with the recent constructional trend. Though the automatic monitoring system is more useful and advanced than manual monitoring system, accuracy of the system is not verified sufficiently. It was examined that the reliance of automatic monitoring system in this paper through the comparison of monitoring result obtained one of deep urban excavation site in which the each type of monitoring system was executed concurrently. Result of the examination is that the two types of monitoring system is generally alike in view of monitoring result, so the engineering reliance of automatic system was confirmed in case site. This study was researched in restricted one case site, so it is expected more precise analysis from security of more data monitored and progressive study.