scholarly journals Time-Frequency Analysis of Partial Discharge Current Pulses in Different Gas Environment under Lightning Impulse

2020 ◽  
Vol 20 (4) ◽  
pp. 196-201
Author(s):  
Kemal Arikan ◽  
Emel Önal ◽  
Serhat Şeker

AbstractThis paper deals with a time-frequency analysis of the measured partial discharge (PD) currents in different insulation gases. These gas environments consist of a pure SF6 (sulphur-hexafluoride) and sulphur-hexafluoride and nitrogen (1 % SF6 + 99 % N2) mixture, under both positive and negative lightning impulse (LI) voltage stresses. In this study, the short time Fourier transform was used to extract the time-frequency information of PDs for different gases at different pressures, and these results were compared to each other. Thus, the relationship between the time, amplitude, and frequency of PD currents was studied. Moreover, some statistical formulas, such as mean, standard deviation, kurtosis, and skewness were applied to the time-dependent PD current data. As a result, a correlation between obtained statistical results and PD frequencies was examined. In most cases, the frequency of partial discharge decreased when the pressure increased. The amplitude of the partial discharges for negative polarity was more than that for positive polarity gas insulations. The partial discharge amplitudes of the pressure of 2 bar were mostly high compared to other pressures. This case demonstrated that SF6 had a maximum minimum character in terms of breakdown. The partial discharge frequency of a 1 % SF6 mixture was higher than that of pure SF6. It is thought that SF6 suppresses the discharge frequency, and statistical evaluations support the experimental results.

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki

2013 ◽  
Vol 798-799 ◽  
pp. 561-564
Author(s):  
Ji Yu Zhou ◽  
Feng Dao Zhou

Sea is rich in oil and gas resources, the marine controlled source electromagnetic method (CSEM) is a kind of method seabed oil gas geophysical technology rising in recent years. Because of the problem of CSEM about the air wave in the shallow water, the research of time-frequnecy analysis technique is used to suppress the air wave in this paper. The basic idea is: because of the CSEM signals speed are different in the air and submarine, so the time which received by the receiving points are also different through these two kinds of ways. Using the time-frequency analysis technique and theoretical calculation, we can determine which part of the signal is spread over the ocean, so as to suppress the air wave effectively. This paper lists several methods of time-frequency analysis, such as Short-time Fourier transform, W-V distribution, Wavelet transform, Hilbert Huang transform. Through the time-frequency graph,we get the conclusion that HHT is better than others in concentration degree,and W-V distribution is better than STFT.Compared with the original signal, the time-frequency graph is the best in using Smooth Puseudo W-V Distribution.I have a detailed analysis about real case in using SPWVD at last.


2000 ◽  
Vol 21 (2) ◽  
pp. 229-240 ◽  
Author(s):  
Sigrid Elsenbruch ◽  
Zhishun Wang ◽  
William C Orr ◽  
J D Z Chen

2016 ◽  
Vol 20 (8) ◽  
pp. 1143-1154
Author(s):  
Zuo-Cai Wang ◽  
Feng Wu ◽  
Wei-Xin Ren

The stationarity test of vibration signals is critical for the extraction of the signal features. In this article, the surrogate data with various time–frequency analysis methods are proposed for stationary test of vibration signals. The surrogate data are first generated from the Fourier spectrum of the original signal with keeping the magnitude of the spectrum unchanged and replacing its phase by a random sequence. The local and global spectra of the original signal and the surrogate data are then estimated by four time–frequency analysis methods, which are short-time Fourier transform, multitaper spectrograms, wavelet transform, and S-transform methods. The index of nonstationarity is then defined based on the distances between the local and global spectra. Three kinds of synthetic signals, which are stationary signals, frequency-modulated signals, and amplitude-modulated signals, are tested to compare the efficiency of the four time–frequency analysis methods as mentioned. The results show that with a certain observation scale value, the index of nonstationarity based on the short-time Fourier transform or wavelet transform method may fail to test the stationarity of the signal. The parametric studies and sensitivity analysis of the observation scale and noise-level effect are also extensively conducted. The results show that the index of nonstationarity calculated using the multitaper spectrograms’ method is more suitable for stationarity test of frequency-modulated signals, while the index of nonstationarity calculated using the S-transform method is more suitable for stationarity test of amplitude-modulated signals. The results also show that the noise has a significant effect on the stationarity test results. Finally, the stationarity of a real vibration signal measured from a cable is tested, and the results show that the proposed index of nonstationarity can effectively test the stationarity of real vibration signals.


2014 ◽  
Vol 684 ◽  
pp. 124-130
Author(s):  
Hong Li ◽  
Qing He ◽  
Zhao Zhang

There is very rich fault information in vibration signals of rotating machineries. The real vibration signals are nonlinear, non-stationary and time-varying signals mixed with many other factors. It is very useful for fault diagnosis to extract fault features by using time-frequency analysis techniques. Recent researches of time-frequency analysis methods including Short Time Fourier Transform, Wavelet Transform, Wigner-Ville Distribution, Hilbert-Huang Transform, Local Mean Decomposition, and Local Characteristic-scale Decomposition are introduced. The theories, properties, physical significance and applications, advantages and disadvantages of these methods are analyzed and compared. It is pointed that algorithms improvement and combined applications of time-frequency analysis methods should be researched in the future.


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