• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.848-859
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• 2016

System failures in thermal power plants (TPPs) can lead to serious losses because the equipment is operated under very high pressure and temperature. Therefore, it is indispensable for alarm systems to inform field workers in advance of any abnormal operating conditions in the equipment. In this paper, we propose a clustering-based fault detection method for steam boiler tubes in TPPs. For data clustering, k-means algorithm is employed and the number of clusters are systematically determined by slope statistic. In the clustering-based method, it is assumed that normal data samples are close to the centers of clusters and those of abnormal are far from the centers. After partitioning training samples collected from normal target systems, fault scores (FSs) are assigned to unseen samples according to the distances between the samples and their closest cluster centroids. Alarm signals are generated if the FSs exceed predefined threshold values. The validity of exponentially weighted moving average to reduce false alarms is also investigated. To verify the performance, the proposed method is applied to failure cases due to boiler tube leakage. The experiment results show that the proposed method can detect the abnormal conditions of the target system successfully.

• 한국초전도학회:학술대회논문집
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• v.15
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• pp.20-20
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• 2005

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.4
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• pp.355-360
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• 2013

With the modern machinery towards the direction of high-speed development, the thermal issues of mechanical transmission system and its components is increasingly important. Ball bearing is one of the main parts in rotating machinery system, and is a more easily damaged part. In this paper, bearing thermal fault detection is investigated in details Using infrared thermal imaging technology to the operation state of the ball bearing, a preliminary thermal analysis, and the use of numerical simulation technology by finite element method(FEM) under thermal conditions of the bearing temperature field analysis, initially identified through these two technical analysis, bearing a temperature distribution in the normal state and failure state. It also shows the reliability of the infrared thermal imaging technology. with valuable suggestions for the future bearing fault detection.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.705-712
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• 2003

Analysis for the thermal stress distribution in the laminated plates containing a hot-spot(local heating region) is performed. It is assumed that the local heating region induces only mechanical stress by the thermal expansion but effect of the thermal conduction is neglected. The region is regarded equivalent to a homogeneous inclusion expanding in a laminated medium. As an example, Au/YBCO/Al$_2$O$_3$laminate which is often employed for High Temperature Superconducting Fault Current Limiter(HTS FCL) has been analyzed. Effects of heat input, thickness of each layer and the got spot size upon the stress distribution in the hot-spot have been investigated. For a constant heat generation into the hot-spot, as the thickness of the Al$_2$O$_3$substrate increases, the stress in the YBCO layer is peculiarly oscillated, and the curvature of laminate has a maximum at a certain thickness of the Al$_2$O$_3$.

• Progress in Superconductivity and Cryogenics
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• v.4 no.1
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• pp.30-34
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• 2002

In this Paper, Insulation of current lead in the conduction-cooled DC reactor for the 1.2kV class 3 high-Tc superconducting fault current limiter(SFCL) is studied. Thermal link which conducts heat energy but insulates electrical energy is selected as a insulating device for the current lead in the conduction-cooled Superconducting DC reactor. It consists of oxide free copper(OFC) sheets, Polyimide films, glass fiberglass reinforced Plastics (GFRP) plates and interfacing material such an indium or thermal compound. Through the test of dielectric strength in L$N_2$, polyimide film thickness of 125 ${\mu}{\textrm}{m}$ is selected as a insulating material. Electrical insulation and heat conduction are contrary to each other. Because of low heat conductivity of insulator and contact area between electrical insulator and heat conductor, thermal resistance of conduction-cooled system is increased. For the reducing of thermal resistance and the reliable contact between Polyimide and OFC, thermal compound or indium can be used As thermal compound layer is weak layer in electrical field, indium is finally selected for the reducing of thermal resistance. Thermal link is successfully passed the test. The testing voltage was AC 2.5kVrms and the testing time was 1 hour.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.965-973
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• 2022

As IoT(Internet of Things) devices become common, many algorithms have been developed to protect users' personal information. The laser fault injection attack that threatens those algorithms is a side-channel analysis that intentionally injects a laser beam to the outside of a device to acquire confidential information or abnormal privileges of the system. There are many studies to determine the timing of fault injection to reduce the number of necessary fault injections, but the location to inject faults is only repeatedly searched for the entire area of the device. However, when fault injection is performed in an algorithm-independent area, the attacker cannot obtain the intended faulted statement or attempt to bypass authentication, so finding areas vulnerable to fault injection and performing an attack is an important consideration in achieving a high attack success rate. In this paper, we show that a 100% attack success rate can be achieved by determining the vulnerable areas for fault injection by using electromagnetic and thermal information generated from the device's chip. Based on this, we propose an efficient fault injection attack system.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2002.02a
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• pp.300-302
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• 2002

In this paper the high-speed fault current detector for superconducting fault current limiter is described. Detecting and interrupting the fault currents as quickly as possible is required in order not to exceed the thermal capacity of superconducting fault current limiter. A detecting method of an instantaneous fault current magnitude is adopted in the equipment described in this paper and a current signal through an analog/digital(A/D) converter would be compared with the reference in the digital signal processor(DSP). Around 20ms has elapsed for detecting the fault current. It is necessary to establish the appropriate trade-off between the reliability and detection speed.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.1-8
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• 2004

In this paper, we propose neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, ART2 neural network is used for fault isolation. The performance and effectiveness of the proposed ART2 neural network based fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.615-620
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• 2015

This paper deals with a fault detection system design for a boiler-turbine control system of thermal power plant. We described the nonlinear properties of the boiler-turbine dynamics as a T-S fuzzy system with time varying measurable parameters. We design a residual generator using an observer based fault detection filter. In order to identify the faulted output sensor, an approximate inverse system is connected to the outport of the fault detection filter. We demonstrate the efficiency of the suggested design method via computer simulations.