• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2570-2575
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• 2003

Monitoring a power transmission line is significant for power electric companies. In this paper, we propose a new method for detecting an fault point of power transmission line by use of M-sequence correlation technique. In this method, detecting signal is used as one or plural M-sequences ( same characteristic polynomial, including normal and reverse mark, synchronized ). In receiving point, we make same sequence with the input one and take crosscorrelation function between M-sequence and the received signal. We can see transfer fanctions of plural paths between inputs and a output taps separated from different of delay times on the crosscorrelation function, and from these transfer fanctions, so we compare them when fault occurred with in usual.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.945-948
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• 2005

Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3367-3378
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• 1999

ATM technology, which acts as a representative high-speed bandwidth technology, plays an important role in Internet environment. ATM network, supporting QoS(Quality of Service) and various traffic characters in high speed, configures many VPC(Virtual Path Connection)/VCC(Virtual Channel Connection). It is important to guarantee the QoS of each connection and it is necessary for the network manager to search element affecting the QoS of VPC/VCC and to control ATM network correctly. In the paper, the management information of VPC/VCC, that ATM network manager Using the fault notification for ATM switch, we can manage the configuration, fault and performance of ATM network. Thus, we extracted the configuration, fault and performance monitoring item from the ATM-MIB and SNMP M4 Network Element View MIB. And we designed the ATM network configuration, fault and performance management system based on the extracted item.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1765-1772
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• 2015

The integrity of the gas insulated switchgear (GIS) is vital to the safety of an entire power grid. However, there are some limitations on the techniques of detecting and diagnosing partial discharge (PD) induced by insulation defects in GIS. This paper proposes a joint electro-chemical detection method to resolve the problems of incomplete PD data source and also investigates a new unique fault diagnosis method to enhance the reliability of data processing. By employing ultra-high frequency method for online monitoring and the chemical method for detecting SF6 decomposition offline, the acquired data can form a more complete interpretation of PD signals. By utilizing DS evidence theory, the diagnostic results with tests on the four typical defects show the validity of the new fault diagnosis system. With higher accuracy and lower computation cost, the present research provides a promising way to make a more accurate decision in practical application.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.11
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• pp.572-576
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• 2006

As the increasing of capacity and technology of power facilities, rotating machines such as turbine generators and water turbines are getting higher at capacity but smaller in size. Thus the monitoring and diagnosis of generators for fault detection and protection has attracted intensive interest. Most of electrical faults of rotating machines appear in their windings. In case of an after-fault in high capacity rotating machines, the recovering cost is usually very expensive and additional time is necessary for returning in a normal situation. In this paper, the magnetic flux patterns in air-gap of a generator under various fault states as well as a normal state are simulated by a conventional FEM tool. These results are successfully applied to detection and diagnosis of the short-circuit condition in rotor windings of a high capacity generator.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.582-587
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• 2011

Acoustic Emission(AE) is widely used for early detection of faults for rotating machinery in these days because of its high sensitivity. AE signal has to need for transferring to low frequency range for the spectrum analysis included the fault mechanism. In transferring process, we lose a lot of fault information caused by unusable signal processing method. Discrete Wavelet Transform(DWT) is a method of signal processing for AE signatures, but the pattern of its mother function is not optimized with AE signals. So, we can lose the fault information when we want to use the DWT for AE signal. Therefore, in this paper, we will propose a novel pattern for DWT mother function, which is optimized with AE signals. And it will be applied to compare the results of DWT by daubechie and novel pattern.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.905-910
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• 2008

Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.833-834
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• 2014

In recent years, a pattern recognition method has been widely used by researchers for fault diagnoses of mechanical systems. A pattern recognition method determines the soundness of a mechanical system by detecting variations in the system's vibration characteristics. Hidden Markov model has recently been used as pattern recognition methods in various fields. In this study, a HMM method for the fault diagnosis of a mechanical system is introduced, and a rotating machine with mass unbalance is selected for fault diagnosis. Moreover, a diagnosis procedure to identity the size of a defect is proposed in this study.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.268-277
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• 1999

Impulsive acoustic and vibration signals within gear are often induced by impacting of fault tooths in gear. Thus the detection of these impulses can be useful for fault diagnosis. Recently there is an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals then to increase the kurtosis values. We show that the fourth order Wigner Moment Spectrum, called the Wigner Trispectrum, has found superior detection performance to second order Wigner distribution for typical impulsive signals in a condition monitoring application. These methods are also applied to data sets measured within an industrial gear box.

• Journal of the Korean Society of Safety
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• v.21 no.1 s.73
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• pp.6-14
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• 2006

The development of automatic production systems have required intelligent diagnostic and monitoring functions to overcome system failure and reduce production loss by the failure. In order to perform accurate operations of the intelligent system, implication about total system failure and fault analysis due to each mechanical component failures are required. Also solutions for repair and maintenance can be suggested from these analysis results. As an essential component of a mechanical system, a bearing system is investigated to define the failure behavior. The bearing failure is caused by lubricant system failure, metallurgical deficiency, mechanical condition(vibration, overloading, misalignment) and environmental effects. This study described slab transfer equipment fault train due to stress variation and metallurgical deficiency from lubricant failure by using FTA.