• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.670-675
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• 1994

Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

• 전기학회논문지
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• 제56권7호
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• pp.1191-1198
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• 2007

In this paper, the fault detection and noise cancellation algorithm based on wavelet transform was developed to locate the fault more accurately. Specially, noise cancellation algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault detection, classification and location algorithm were tested by EMTP simulation on real power cable system. From these results, the faults can be detected and located even in very difficult situations, such as at different inception angle and fault resistance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• 전기학회논문지
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• 제61권6호
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• pp.910-915
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• 2012

In this paper we propose multi-grounded neutral design method which was considered of transferred transient overvoltage when line to neutral fault occurs. Specially, In order to confirm the actual transient overvoltage magnitude which occurs on neutral line, we considered some screening(shielding) effects. The screening coefficient was deducted from field test results and calculation in a distribution line which is identical with an actual power line. The purpose of this paper is to attempt to suggest the guidance for grounding skystem design considering limitation of overvoltage for LV side in IEC 61936. The result is based on EMTP simulation and real field faults situation in distribution lines.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.882-885
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• 2011

This paper presents testing and self-calibration of RF circuits using MEMS switches to identify process-related defects and out of specification circuits. We have developed a novel multi-tone dither test technique where the test stimulus is generated by modulating the RF carrier signal with a multi-tone signal generated using an Arbitrary Waveform Generator (AWG) with additive white Gaussian noise. This test stimulus is provided as input to the RF circuit and peak-to-average ratio (PAR) is measured at the output. For a faulty circuit, a significant difference is observed in the value of PAR as compared to a fault-free circuit. Simulation is performed for various circuit conditions such as fault-free as well as fault-induced and their corresponding PARs are stored in the look-up table. This testing and self-calibration technique is exhaustive and efficient for present-day communication systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.217-219
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• 2003

This paper presents a distance relaying algorithm for a transmission line protection with MAS. First, the voltage and fault current of the opposite side are represented as a function of those of the measuring end using source voltages of both ends. These voltages are assumed to be obtained from the transformers protecting agents, periodically in normal state. Then, the fault location expression, independent of fault resistance, is derived with voltage and current in only one end of faulted line used. The suggested algorithm is applied to a simple system with two power sources to show its effectiveness.

• Progress in Superconductivity
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• 제7권2호
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• pp.114-119
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• 2006

High critical current density, high n value, multiple faults endurances, and fast recovery characteristics of YBCO thin films are very attractive characteristics for developing resistive type superconducting fault current limiters. But due to the limited current and voltage ratings of one YBCO module, it is needed to construct series and parallel module connections for high capacity electric networks. Especially for distribution network, more than 30 units should be connected in series to meet voltage level. So in order to construct distribution-level superconducting fault current limiter, simultaneous quench in one YBCO thin films should be realized, and furthermore, quench should be occurred in all fault current limiting units equally to avoid local heating and failures. In this paper, we proposed optimum design of YBCO thin films for fault current limiting module and technical method using shunt resistor to achieve simultaneous quench between multi current limiting units. From the analytical and the experimental results, optimal current path and thickness of shunt material was determined for YBCO thin films and shunt resistor between modules was developed. Finally, 14 kV one phase resistive fault current limiter using multi YBCO thin films was constructed and it was possible to get satisfactory test results.

• 대한기계학회논문집A
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• 제34권11호
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• pp.1681-1689
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• 2010

Support Vector Machine(SVM)을 이용한 회전기계 진단 연구가 많이 수행되어 왔으나 결함 분류성능은 입력 특징과 더불어 다중 분류 방법, 이진분류기, 커널함수 등에 따라 다르다. SVM 을 이용한 대부분의 기존 연구들은 한번 입력 특징들을 선정하면 결함 분류시 동일한 특징데이터를 이용한다. 본 논문에서는 회전기계의 다양한 결함조건에서 측정한 진동신호로부터 추출한 통계적 특징들을 이용하여 각각의 결함을 분류하기 위한 최적 특징들을 선정한 후, 해당 결함상태를 분류하기 위한 SVM 학습과 분류에 각각 이용하였다. 실험자료를 이용한 검증 결과, 제안한 단계 분류 방법이 상대적으로 적은 학습시간으로 단일 다중 분류 방법과 유사한 분류 성능을 얻을 수 있었다.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권2호
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• pp.103-110
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• 2005

Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different load conditions. Multiple Discriminant Analysis (MDA) and Artificial Neural Networks (ANN) provide appropriate environments to develop such fault detection schemes because of their multi-input processing capabilities. This paper describes two fault detection schemes for broken rotor bar fault detection with multiple signature processing, and demonstrates that multiple signature processing is more efficient than single signature processing.

• 한국정보처리학회논문지
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• 제7권7호
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• pp.2169-2178
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• 2000

This paper proposes the structure of an agent and rules for fault detection and location on LAN. To find out a reason of critical fault incurred LAN, collision detection rule, error detection rule, broadcast detection rule, system location rule, and Internet application location rule ar shown. Also, the structure of multi-agent system and state transition diagram is portrayed to have connectivity with he set of rules. To verify availability of proposed rules, the process to find a faulty system is shown by monitoring and analyzing the LAN fault occurrences from the proposed set of rules. Such an rule based agent system is helpful to an Internet manager to solve a reason of fault and make ad decision from gathering management information.