• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.499-502
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• 2014

This paper presents a comparison study between simulation and experiment for fault diagnostics of a spur gear. In simulation, fault diagnostics using transmission error (TE) was performed and concluded to be valid. In a real experiment, however, it is not as easy to detect faults of gears using TE as in simulation. In this paper, after seeding the various faults like tooth crack of different length, tooth breakage and spalling in test rig, TE was calculated. Then, several signal processing techniques were performed to overcome the limitations of an experiment in detecting the fault signals of TE. After signal processing, we could detect the various faults of spur gears and different amplitude of TE sparks from cracks of different length. Then we discussed the difference between simulation and experment.

• Journal of Electrical Engineering and Technology
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• 제7권5호
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• pp.797-806
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• 2012

Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

• 한국컴퓨터정보학회논문지
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• 제21권10호
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• pp.125-133
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• 2016

In this paper, we propose a real-time fault monitoring and dual system design of the countdown time-generating system, which is the main component of the mission control system. The countdown time-generating system produces a countdown signal that is distributed to mission control system devices. The stability of the countdown signal is essential for the main launch-related devices because they perform reserved functions based on the countdown time information received from the countdown time-generating system. Therefore, a reliable and fault-tolerant design is required for the countdown time-generating system. To ensure system reliability, component devices should be redundant and faults should be monitored in real time to manage the device changeover from Active mode to Standby mode upon fault detection. In addition, designing different methods for mode changeover based on fault classification is necessary for appropriate changeover. This study presents a real-time fault monitoring and changeover system, which is based on the dual system design of countdown time-generating devices, as well as experiment on real-time fault monitoring and changeover based on fault inputs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1376-1378
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• 1999

Most conventional protection relays are based on processing information in the spectrum that is close to or at power frequency. It is, however, widely known that faults on transmission lines produce frequency components of a wide range In this respect, this paper describes the basis of a Protection technique for transmission lines which utilises high-frequency components. Fault-generated signals caused by post-fault and the signal derived from stack tuner is connected to the coupling capacitor of CVT. Digital signal processing is then applied to the captured information to determine whether the fault is inside or outside the Protected zone, and to discriminate the fault type on transmission line.

• Journal of Advanced Marine Engineering and Technology
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• 제30권2호
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• pp.247-252
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• 2006

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• 전기학회논문지P
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• 제67권3호
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• pp.119-124
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• 2018

Recently, LVDC distribution network and DC microgrid with many advantages are being built. However, this LVDC distribution is an IT grounded or ungrounded system, and it is difficult to detect a ground fault because the fault current is small. In this paper, we propose a signal injection method for unipolar LVDC distribution network to detect ground fault in ungrounded LVDC distribution, and various analyzes were performed for ground fault detection.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.281-286
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• 2005

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.883-887
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• 2002

We should maintain the maximum operation capacity for production facilities and find properly out the fault of each equipment rapidly in order to decrease a loss caused by its failure. The acoustic and vibration signals of a machine always carry the dynamic information of the machine. These signals are very useful fur the feature extraction and fault diagnosis. We performed a fundamental study which develops a system of fault diagnosis for a pump. We experimented vibrations by acceleration sensors and noises by microphones, compared and analysed for normal products, artificially deformed products. We tried to search a change of the dynamic signals according to machine malfunctions and analyse the type of deformation or failure. The results showed that acoustic signals as well as vibration signals can be used as a simple method lot a detection of machine malfunction or fault diagnosis.

• 디지털산업정보학회논문지
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• 제14권3호
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• pp.39-44
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• 2018

Communication in real-time distributed system should have high reliability. To develop group communication Protocol with high reliability, potential fault should be known and when fault occurs, it should be detected and a necessary action should be taken. Existing detection method by Ack and Time-out is not proper for real time system due to load to Ack which is not received. Therefore, group communication messages from real-time distributed processing systems should be communicated to all receiving processors or ignored by the message itself. This paper can make be sure of transmission of reliable message and deadline by suggesting and experimenting fault detection technique applicable in the real time distributed system based on ring, and analyzing its results. The experiment showed that the shorter the cycle of the heartbeat signal, the shorter the time to propagate the fault detection, which is the time for other nodes to detect the failure of the node.