• International Journal of Aeronautical and Space Sciences
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• 제9권2호
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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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• 한국추진공학회 2008년 영문 학술대회
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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.

• Journal of information and communication convergence engineering
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• 제5권1호
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• pp.7-11
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• 2007

The aim of this paper is to design and implement a new ECG signal monitoring and analysis method for the home care of elderly persons or patients, using wireless sensor network (WSN) technology. The wireless technology for home-care purpose gives new possibilities for monitoring of vital parameter with wearable biomedical sensors and will give the patient freedom to be mobile and still be under continuously monitoring. Developed platform for portable real-time analysis of ECG signals can be used as an advanced diagnosis and alarming system. The ECG features are used to detect life-threatening arrhythmias, with an emphasis on the software for analyzing the P-wave, QRS complex, and T-wave in ECG signals at server after receiving data from base station. Based on abnormal ECG activity, the server transfer diagnostic results and alarm conditions to a doctor's PDA. Doctor can diagnose the patients who have survived from arrhythmia diseases.

• Journal of Chest Surgery
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• 제57권2호
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• pp.205-212
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• 2024

Background: Postoperative atrial fibrillation (A-fib) is a serious complication of cardiac surgery that is associated with increased mortality and morbidity. Traditional 24-hour Holter monitors have limitations, which have prompted the development of innovative wearable electrocardiogram (ECG) monitoring devices. This study assessed a patch-type wearable ECG device (MobiCARE-MC100) for monitoring A-fib in patients undergoing cardiac surgery and compared it with 24-hour Holter ECG monitoring. Methods: This was a single-center, prospective, investigator-initiated cohort study that included 39 patients who underwent cardiac surgery between July 2021 and June 2022. Patients underwent simultaneous monitoring with both conventional Holter and patchtype ECG devices for 24 hours. The Holter device was then removed, and patch-type monitoring continued for an additional 48 hours, to determine whether extended monitoring provided benefits in the detection of A-fib. Results: This 72-hour ECG monitoring study included 39 patients, with an average age of 62.2 years, comprising 29 men (74.4%) and 10 women (25.6%). In the initial 24 hours, both monitoring techniques identified the same number of paroxysmal A-fib in 7 out of 39 patients. After 24 hours of monitoring, during the additional 48-hour assessment using the patch-type ECG device, an increase in A-fib burden (9%→38%) was observed in 1 patient. Most patients reported no significant discomfort while using the MobiCARE device. Conclusion: In patients who underwent cardiac surgery, the mobiCARE device demonstrated diagnostic accuracy comparable to that of the conventional Holter monitoring system.

• Proceedings of the KAIS Fall Conference
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• 한국산학기술학회 2002년도 추계학술발표논문집
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• pp.178-180
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• 2002

In this Paper, we conducted a experimental study to measure a particle size distribution and mass spectrum with the special instrument such as ISPM and Q-MS. Also, we set up a total measuring system for monitoring the particle in the process chamber.

• Proceedings of the KIEE Conference
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.275-277
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• 2001

In this paper a preventative and diagnostic system for high and ultra high voltage electric power transmission apparatus is proposed to secure substation normal operation. The proposed system consists of monitoring sub-system and diagnostic sub-system, which are mainly for GIS and main transformer, and the system will be applied for newly established 765kV class substation in Korea. Some guideline for combination with substation control system are presented, and engineering solution as an improved substation automation system is also proposed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 한국추진공학회 2010년도 제34회 춘계학술대회논문집
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• pp.295-299
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• 2010

Recently, development and application of the condition monitoring and diagnostic system for improvement of durability and reliability and reduction of operating cost is generalized in the aircraft propulsion system. Especially, for reliable operation of the UAV which is flying in high altitude more than 40,000 ft for a long time an condition monitoring system to identify faults and degradations of its propulsion system should be needed. Therefore, this work proposes an on-line condition monitoring program using MATLAB/SIMULINK. In the development phase of the program, a engine signal generation module is used to simulate real engine measuring parameters instead of the real engine. The proposed on-line condition monitoring program was applied to a real turboprop engine to validate its application capability.

• Tribology and Lubricants
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• 제36권6호
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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.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 한국전기전자재료학회 2010년도 하계학술대회 논문집
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• pp.116-116
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• 2010

This paper introduces an comprehensive monitoring and management program for implementation of a real-time monitoring system that monitors condition of urban railway AC/DC transformers, disconnecting switches, circuit breakers, regulators, and GIS (Gas Insulated Switchgear). Especially, the system is applied to diagnose the overall condition of urban railway substations by sending acquired data through an OPC server to a database, effectively storing and monitoring conditions simultaneously. The above system is a management based system and is also applicable to small-scale systems.

• Journal of the Korean Institute of Educational Facilities
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• 제27권1호
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• pp.3-10
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• 2020

Due to the frequent occurrence of large-scale disasters such as recent earthquakes, the problem of the safety of old school buildings has emerged. The need to secure safety management technology through constant monitoring is increasing in an attempt to supplement old school buildings with weak disaster response capabilities. Traditional research is approaching the development of an existing sensor-based risk precursor information monitoring system. However, unlike this, in this study, we will focus on the development of a data analysis platform as part of the development of a continuous monitoring system that can be prepared for earthquakes, collapses, and fires, based on constantly measured data. For this reason, the development of a safety diagnostic algorithm based on the optimal sensor-attached points and sensor data reflecting the fragile characteristics of old school buildings was derived. Utilizing this, a message and action manual system for each management / use entity of school buildings after retirement was constructed.