• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.308-314
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• 2003

This paper presents a serial communication based fault diagnosis scheme for a brushless DC (BLDC) motor using parameter estimation and Bayes classifier. The presented scheme consists of a smart network board, and a fault detection and isolation (FDI) master. The smart network board is installed near the BLDC motor drive system to acquire motor data and transmit motor data to the FDI-master via serial communication channel. The FDI-master estimates BLDC motor resistance to detect symptom of faults, and assign symptom to fault type using Bayes classifier. In this scheme, since communication time delay has a serious effect on performance, periodic and fixed communication protocol is designed. Hence, the delay time is priory known. By experiment result, presented scheme was verified.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2212-2219
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• 2018

This paper describes extended fault location algorithm using estimated remote source impedance. The method uses data only at the local end and the sequence current distribution factors for more accurate estimation. The proposed algorithm can respond to variation of the local and remote source impedance. Therefore, this method is especially useful for transmission lines interconnected to a wind farm that the source impedance varies continuously. The proposed algorithm is very insensitive to the variation in fault distance and fault resistance. The simulation results have shown the accuracy and effectiveness of the proposed algorithm.

• Convergence Security Journal
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• v.13 no.1
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• pp.3-10
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• 2013

In this paper, reliability software model considering fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the S-shaped distribution model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model was used. In a software failure data analysis considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of failure time data and reliability make out.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.599-604
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• 2017

Nowadays reactance method is being used as a technique for fault location in parallel feeding AC traction power system. However, implementation of this method requires a large number of field tests(ground fault) which is a huge burden on the operators. This paper presents a new estimation technique using quadratic interpolation to reduce number of times for field test and improves the accuracy of fault location. To verify a new technique, we solve AT feeding circuit and model it using PSCAD/EMTDC. Finally this paper conducts a comparative analysis of usefulness between a new technique and real field data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1492-1501
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• 2011

A wide-area protection intelligent technique has been used to improve a reliability in power systems and to prevent a blackout. Nowadays, voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in power systems. As this technique has the difficulties in collecting and sharing of information, there have been used a FNET method for the wide-area intelligent protection. This technique is very useful for the prediction of the inception fault and for the prevention of fault propagation with accurate monitoring frequency and frequency deviation. It consists of FDRs and IMS. It is well known that FNET can detect the dynamic behavior of system and obtain the real-time frequency information. Therefore, FDRs must adopt a optimal frequency estimation method that is robust to noise and fault. In this paper, we present comparative studies for the frequency estimation method using IRDWT(improved recursive discrete wavelet transform), for the frequency estimation method using FRDWT(fast recursive discrete wavelet transform). we used the Republic of Korea 345kV power system modeling data by EMTP-RV. The user-defined arbitrary waveforms were used in order to evaluate the performance of the proposed two kinds of RDWT. Also, the frequency variation data in various range, both large range and small range, were used for simulation. The simulation results showed that the proposed frequency estimation technique using FRDWT can be the optimal frequency measurement method applied to FDRs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1758-1764
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• 2012

A large number of wire rope has been used in various inderstiries as Cranes and Elevators from expanding the scale of the industrial market. But now, the management of wire rope is used as manually operated by rope replacement from over time or after the accident.It is caused to major accidents as well as economic losses and personal injury. Therefore its time to need periodic fault diagnosis of wire rope or supply of real-time monitoring system. Currently, there are several methods has been reported for fault diagnosis method of the wire rope, to find out the feature point from extracting method is becoming more common compared to time wave and model-based system. This method has implemented a deterministic modeling like the observer and neural network through considering the state of the system as a deterministic signal. However, the out-put of real system has probability characteristics, and if it is used as a current method on this system, the performance will be decreased at the real time. And if the random noise is occurred from unstable measure/experiment environment in wire rope system, diagnostic criterion becomes unclear and accuracy of diagnosis becomes blurred. Thus, more sophisticated techniques are required rather than deterministic fault diagnosis algorithm. In this paper, we developed the fault diagnosis of the wire rope using probability density estimation techniques algorithm. At first, The steady-state wire rope fault signal detection is defined as the probability model through probability distribution estimate. Wire rope defects signal is detected by a hall sensor in real-time, it is estimated by proposed probability estimation algorithm. we judge whether wire rope has defection or not using the error value from comparing two probability distribution.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.311-320
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• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Journal of the Korea Safety Management & Science
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• v.11 no.1
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• pp.87-91
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• 2009

본 논문은 상대적으로 새로운 기법인 Parzen Density Estimation과 Multi-class SVM을 이용한 지능형 고장 탐색과 진단 방법을 제안하고 있다. 본 연구에서는 롤링 베어링을 대상으로 고장을 탐색하고 진단하기 위한 방법을 제안하는데 Parzen Density Estimation과 Multi-class SVM은 고장 클래스를 잘 표현할 수 있다. Parzen Density Estimation은 새로운 패턴 데이터의 거절과 알려진 데이터 패턴의 밀도의 평가에 의해 새로운 패턴을 찾아낼 수 있고, Multi-class SVM 기반의 방법은 여러 클래스의 고장을 support vector로 표현하여 고장 패턴을 찾아낼 수 있다. 본 연구에서는 실제의 다중 클래스를 가지는 롤링 베어링의 고장 데이터를 사용하여 고장 패턴을 탐색하는 과정을 보여주는데, 커널함수의 적절한 파라미터의 선택에 의한 Multi-class SVM 기반의 방법이 multi-layer perceptron이나 Parzen Density Estimation 방법보다 우수함을 입증한다.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.26-30
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• 2009

In this paper, a robust model based fault detection for varying temperature is proposed, To develop a robust force estimation model, it needs temperature information because the force sensor's output is affected by a temperature variation. If an EPB system does not include a temperature sensor, the model has a much larger error than an EPB system with a built-in temperature sensor. Therefore, the temperature is estimated by using Ohm's law. The force model is applied with a motor current, battery voltage, operation mode, and the estimated temperature to detect a force sensor's abnormal signal fault. The residual is calculated by comparing the value of the measured force and the estimated force. Fault information is collected by using the output of the evaluated residual with the adaptive thresholds. A proposed robust model based fault detection for varying temperature was verified by HILS (Hardware in the Loop Simulation).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1294-1303
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• 2009

This paper presents a new numerical algorithm for fault discrimination and fault location estimation when occur to arcing ground and arcing line to line on transmission lines. The object of this paper is developed from new numerical algorithm to calculate the fault distance and simultaneously to make a distinction between transient and permanent faults. so the first of object for propose algorithm would be distinguish the permanent from the transient faults. This arcing fault discrimination algorithm is used if calculated value of arc voltage amplitude is greater than product of arc voltage gradient and the length of the arc path, which is equal or greater than the flashover length of a suspension insulator string[1-3]. Also, each algorithm is separated from short distance and long distance. This is difference to with/without capacitance between short to long distance. To test the validity of the proposed algorithms, the results of algorithm testing through various computer simulations are given. The test was simulated in EMTP/ATP simulator under a number of scenarios and calculate of algorithm was used to MATLAB.