• 한국소음진동공학회논문집
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• 제23권9호
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• pp.814-822
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• 2013

For the fault diagnosis of a mechanical system, pattern recognition methods have being used frequently in recent research. Hidden Markov model(HMM) and artificial neural network(ANN) are typical examples of pattern recognition methods employed for the fault diagnosis of a mechanical system. In this paper, a hybrid method that combines HMM and ANN for the fault diagnosis of a mechanical system is introduced. A rotating blade which is used for a wind turbine is employed for the fault diagnosis. Using the HMM/ANN hybrid model along with the numerical model of the rotating blade, the location and depth of a crack as well as its presence are identified. Also the effect of signal to noise ratio, crack location and crack size on the success rate of the identification is investigated.

• 전기학회논문지
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• 제59권9호
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• pp.1673-1679
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• 2010

A photovoltaic (PV) generator is significantly regarded as one important alternative of renewable energy systems recently. Fault detection and diagnosis of engineering dynamic systems is a fundamental issue to timely prevent unexpected damages in industry fields. This paper presents an intelligent monitoring approach and fault detection technique for PV generator systems by means of artificial neural network and statistical signal detection theory. We devise a multi-Fourier neural network model for representing dynamics of PV systems and apply a general likelihood ratio test (GLRT) approach for investigating our decision making algorithm in fault detection and diagnosis. We make use of a test-bed of ubiquitous sensor network (USN) based PV monitoring systems for testing our proposed fault detection methodology. Lastly, a real-time experiment is accomplished for demonstrating its reliability and practicability.

• 한국군사과학기술학회지
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• 제9권3호
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• pp.132-140
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• 2006

In this paper, a new fault detection method for the extended Kalman filter, which uses a N-step predictor, is proposed. The N-step predictor performs the only time propagations for N-step intervals without measurement updates and its output is used as a monitoring signal for the fault detection. A consistency between the extended Kalman filter and the N-step predictor is tested to detect a fault. A test statistic is defined by the difference between the extended Kalman filter and the N-step predictor. The proposed method is applied to strapdown inertial navigation system (SDINS). By computer simulation, it is shown that the proposed method detects a fault effectively.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.440-441
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• 2006

The fault location algorithm based on wavelet transform was developed to locate the fault more accuracy after the operation of relay. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. The algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault location algorithm was tested by simulation on real power cable system. From these results, the fault can be located even in very difficult situations, such as at different inception angle and fault resistance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.226-229
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• 2001

The combined transmission lines with the underground power cables are continuously expanded in power systems. So the fault of combined transmission line is increased every year as the complication of underground transmission line. In this paper. traveling wave theory and DWT wavelet transform are used for fast and accurate detection of fault location at the combined transmission line. Traveling wave travels to each bus like surge and repeats reflection and transmission till transient signal is completely disappeared. When fault is occurred on overhead and underground tine, the fault location detecting algorithm was performed with using continuous peak value time-delay of traveling wave reflected from A bus.

• 대한기계학회논문집A
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• 제24권7호
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• pp.1731-1739
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• 2000

The Vibration signals of a gear driving system is often associated with gear tooth faults. Many studies have been done on the detection of impulsive vibration signals, which characterize the breaka ge of a gear tooth. Also, most of the studies on gear fault diagnosis are only about the fault existence at one gear-pair. This study concerns on the several possible faults of a geared motor that has three gear pairs. The measurement and analysis on the vibration signals of a running geared motor shows the relationship between the gear faults and the vibration signals. This study also shows that adaptive interference canceling technique can be appropriately applicable to detect which gear-pair has the fault, and that wavelet is better than spectrogram to figure out the gear fault.

• 한국소음진동공학회논문집
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• 제14권8호
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• pp.675-683
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• 2004

The motor current signature provides an important source of the information for the faults diagnosis of three-phase induction motor. The theoretical principles behind the generation of unique signal characteristics, which are indicative of failure mechanisms, are Presented. The fault detection techniques that can be used to diagnose mechanical Problems, stator and rotor winding failure mechanisms, and air-gap eccentricity are described. A theoretical analysis is presented which predicts the presence of unique signature patterns in the current that are only characteristics of the fault. The predictions are verified by experimental results from a special fault Producing test rig and on-site tests in a steel company. And this study have made new diagnostic algorithm for the operating induction motors with the test results. These developments are including the use of monitoring and analysis of electric current to diagnose mechanical and electrical problems and gave the precise test results automatically.

• Nuclear Engineering and Technology
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• 제35권1호
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• pp.25-34
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• 2003

The research on the development of the fault monitoring system for the thermal reduction reactor has been performed preliminarily in order to support the successful operation of the thermal reduction reactor. The final task of the development of the fault monitoring system is to assure the integrity of the thermal$_3$ reduction reactor by the acoustic emission (AE) method. The objectives of this paper are to identify and characterize the fault-induced signals for the discrimination of the various AE signals acquired during the reactor operation. The AE data acquisition and analysis system was constructed and applied to the fault monitoring of the small- scale reduction reactor, Through the series of experiments, the various signals such as background noise, operating signals, and fault-induced signals were measured and their characteristics were identified, which will be used in the signal discrimination for further application to full-scale thermal reduction reactor.

• 조명전기설비학회논문지
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• 제26권3호
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• pp.61-68
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• 2012

This paper deals with a fault diagnosis algorithm for open faults in the switching devices of PWM inverter-fed IPMSM (Interior Permanent Magnet Synchronous Motor) drive. The proposed diagnostic algorithm is realized in the controller using the informations of three-phase currents or reference line-to-line voltages, without requiring additional equipments for fault detection. Under switch open fault conditions, the conventional dq model used to control an AC motor cannot directly be applied for the analysis of drive system, since three-phase balanced condition does not hold. To overcome this limitation, a fault model based on the line-to-line voltages is employed for the simulation studies. For comparative performance evaluation through the experiments, the entire control system is implemented using digital signal processor (DSP) TMS320F28335. Simulations and experimental results are presented to verify the validity of the proposed diagnosis algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2525-2527
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating, so it is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.