• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2442-2447
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• 2015

Because an electric railway vehicle is a large scale moving load, it can cause various kinds of power quality problems in the railroad power system. The power quality impacts are considered as the strong instantaneous stresses to the related power systems and can cause an accelerating aging and a malfunction of the power supplying components. Therefore, it is necessary to detect the small and intermittent symptoms mixed in the voltage waveform. However, they cannot be detected by the triggering functions of the existing power analyzers installed in the railway systems. This paper will examine the drawback of some fast detection tools and propose an advanced detecting and analyzing method based on a combined TEO and STFT algorithm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.1
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• pp.101-106
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• 2004

The phenomenon of PD(Partial Discharge) is accompanied by electromagnetic wave which can be detected by UHF(Ultra High Frequency) antenna. The signals obtaining from UHF antenna are very high rapid pulse and have wide band frequency responses. The distribution of PRPD(Phase Resolved Partial Discharge) which consisted of those pulse train can show distinct characteristics of PD sources. But it is not sufficient to discriminate among PD sources. This paper suggests that the stochastic parameters formed by preprocessing of STFT(Short Time Fourier Transform) are good tools for differentiate from PD sources. The stochastic parameters are CC(Cross Correlation) mean value, CC standard deviation, CC skewness, CC kurtosis.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.243-245
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• 2005

Condition monitoring is desirable for increasing machinery availability, reducing consequential damage, and improving operational efficiency. In this paper, a model-based method using neural network modeling of induction noter in vibration spectra is proposed for machine fault detection and diagnosis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals to continuous spectra so that the neural network model can be trained with vibration spectra. And the faults are detected from changes in the expectation of vibration spectra modeling error. The effectiveness of the proposed method is demonstrated through experimental results.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.67-73
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• 2004

The purpose of this study is to analyze the vibration signal of the revolution machine using the STFT(Short Time Fourier Transform). It is common to analyze the frequency of signal through FFT algorithm with the fixed sampling rate. However, in this situation the order spectrum information useful rather than the general frequency information with the fixed sampling rate. In this paper, the resampling technique was used for getting the information of order spectrum. In resampling process, the arithmetic amount and MSE(Mean Square Error) for various kinds of the signal interpolation was compared and presented the propriety of the interpolation method while developing analysis equipment. Order tracking was implemented using signal interpolation method which it has selected. Then the analyzed results were obtained through simulation using the STFT technique.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.929-940
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• 2006

Early detection and diagnosis of incipient induction machine faults increases machinery availability, reduces consequential damage, and improves operational efficiency. However, fault detection using analytical methods is not always possible because it requires perfect knowledge of a process model. This paper proposes a neural network based expert system for diagnosing problems with induction motors using vibration analysis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals, and the neural network is trained and tested using the vibration spectra. The efficiency of the developed neural network expert system is evaluated. The results show that a neural network expert system can be developed based on vibration measurements acquired on-line from the machine.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.723-730
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• 2015

This paper investigated the noise generation mechanism of a rotary compressor using experimental method. The measurement was carried out for primary parameters which influence noise characteristics. By using STFT(short time Fourier transform), noise sources of a rotary compressor were identified and vibrating modes that increase the noise are verified. Also, it was studied that the correlation between operating speed and noise. Main factors that affect the variation of noise level were considered by the comparison of the experimental results. In addition, a dynamic characteristic of crank shaft was studied and the critical speed was analyzed.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.6
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• pp.451-458
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• 2005

The effects of fiber orientation on acoustic emission(AE) characteristics have been studied for various composite laminates. Reflection and transmission optical microscopy were used to investigate the damage zone of specimens. AE signals were classified through short time Fourier transform(STFT) as different types: AE signals with a high intensity and high frequency band were due to fiber fracture, while weak AE signals with a low frequency band were due to matrix cracking and/or interfacial cracking. Characteristic feature in the rate of hit-events having high amplitudes showed a procedure of fiber breakages, which expressed the characteristic fracture processes of notched fiber-reinforced plastics with different fiber orientations. As a consequence, the behavior of fracture in the continuous composite laminates could be monitored through nondestructive evaluation(NDE) using the AE technique.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.460-467
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• 2008

This paper presents a new numerical algorithm for the fault location estimation and arcing fault detection when a single-phase arcing ground fault occurs on a transmission line. The proposed algorithm derived in the spectrum domain is based on the synchronized voltage and current samples measured from the PMUs(Phasor Measurement Units) installed at both ends of the transmission lines. In this paper, the algorithm uses DFT(Discrete Fourier Transform) for estimation. The algorithm uses a short data window for real-time transmission line protection. Also, from the calculated arc voltage amplitude, a decision can be made whether the fault is permanent or transient. The proposed algorithm is tested through computer simulation to show its effectiveness.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.753-759
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• 2014

In this paper, it is investigated that noise generation mechanism of a rotary compressor using experimental method. The measurement was carried out for primary parameters which influence noise characteristics. By using STFT(short time fourier transform), noise sources of a rotary compressor were identified and vibrating modes that increase the noise are verified. Also, it was studied that the correlation between operating speed and noise. Main factors that affect the variation of noise level were considered by the comparison of the experimental results. In addition, a dynamic characteristic of crank shaft was studied and the critical speed was analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2139-2146
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• 2008

This paper presents a numerical algorithm for fault location estimation which used to data from both end of the transmission line. The proposed algorithm is also based on the synchronized voltage and current phasor measured from the PMUs(Phasor Measurement Units) in the time-domain. This paper has separated from two part of with/without shunt capacitance(short/long distance). Most fault was arc one-ground fault which is 75% over [1]. so most study focused with it. In this paper, the numerical algorithm has calculated to distance for ground fault and line-line fault. In this paper, the algorithm is given with/without shunt capacitance using II parameter line model, simple impedance model and estimated using DFT(Discrete Fourier Transform) and the LES(Least Error Squares Method). To verify the validity of the proposed algorithm, the EMTP(Electro- Magnetic Transient Program) and MATLAB did used.