• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.102-108
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.510-514
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• 2011

To detect the insulator in the fault state on the electric poles, we first measured radiation sounds from normal state insulators and error state insulators in the anechoic chamber. We processed the signals in frequency domain to find the features with filter bank, narrow band and wide band analysis. So we could found two apparent results from their frequency spectrums - one was 120Hz harmonic components, the other was high average noise level than normal state ones. Then we also introduced a technique for the direction detection of the fault state insulator using the cross correlation from the three dimensional array microphones. To eliminate the noise signal from unexpected directions, we suggested the zero padding technique in cross correlation function. From these, we could conclude that acoustic fault detection techniques are useful of the detection of insulators' faults and the estimation of the direction of the fault state insulators.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1233-1240
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• 2004

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the nitration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.3
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• pp.151-158
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• 2013

Large generator of power plant is very important. In order to protect large generator from faults, digital protective relay or IED is required. However, all protective relays for generators of the domestic power plant are operated by foreign products. And now, for technological independence from foreign and improvement of import substitution effect, IEDs using domestic technology are being developed. To evaluate performance of developing next-generation power devices, the study of the dynamic characteristics of the power plant, generator system modeling, fault simulation and analysis, should be considered. Specially, To obtain IEEE Standards COMTRADE format for relay operation test, generator system modeling and fault simulation using PSCAD/EMTDC tools must be preceded. Until now, a complete modeling of generator internal windings and fault simulation techniques dose not exist. In this paper, for evaluation performance of relay elements of developing IED, the generator system modeling and various faults simulation using PSCAD/EMTDC tools were performed. And then, the various transient phenomena through obtained relaying signal of developed modeling were analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.459-462
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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 hon 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.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.178-180
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.350-352
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1037-1043
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• 2004

In this paper, a new fault detection and isolation algorithm fur inertial sensor system is proposed. To identify the inertial sensor fault, single antenna GPS receiver is used as an effective redundancy source. To use GPS receiver as redundancy for the inertial sensors, the algorithm to estimate the attitude and acceleration using single antenna GPS receiver is adopted. By using Doppler shift of carrier phase signal and kinetic characteristics of aircraft, attitude information of aircraft can be obtained at the coordinated flight condition. Based on this idea, fault diagnosis algorithm for inertial sensors using single antenna GPS based attitude is proposed. For more effective FDI, decision variables considering the aircraft maneuver are proposed. The effectiveness of the proposed algorithm is verified through the numerical simulations.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1082-1084
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• 1999

A fault detection of power system must be fast and correctly over input signal without relation to any disturbance. But, it is difficult to detect fault state for digital relay comparison of fault perfectly. In this Paper, we measure each Phase current and infer type of fault using ANFIS(Adaptive Neuro-Fuzzy Inference System).