Leakage current characterization for estimating the conditions of non-ceramic insulators’ surfaces

El-Hag, Ayman H.

doi:10.1016/j.epsr.2006.03.018

Cited by 27 publications

(29 citation statements)

References 6 publications

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“…Further attention has concentrated on separating different components of LCs and on analyzing both the current level and the shape of its waveform. Thus the behavior of LC waveforms has over the last decade been mainly studied in frequency domain with attention paid to correlate LC waveforms with dry band activity, flashover, etc [1][2][3][4][5][6][7][8]. The voltage waveforms are also studied for pollution level monitoring under wetted and contaminated conditions [9].…”

Section: Introductionmentioning

confidence: 99%

Wavelet packet analysis of the applied voltage waveform as a monitoring technique of the outdoor insulation surface

Moula

Mekhaldi

Teguar

2013

2013 IEEE International Conference on Solid Dielectrics (ICSD)

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The objective of our study is to analyse the ac applied voltage signals recorded for different pollution levels using a following technique: wavelet packet analysis. Laboratory tests were performed on flat plate models of glass (500x500x5 mm) under uniform pollution. The plate models were sprayed with a solution prepared by mixing 100 g of kaolin in one liter of distilled water. An appropriate amount of NaCl was added to the slurry to give required Equivalent Salt Deposit Density (ESDD). The various studied ESDD are as follows: 1.2, 3.5, 6, 10, 15 and 20 mS/cm. The obtained results show that this technique constitutes a very effective tool to estimate the pollution severity degree on outdoor insulation surface.

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Section: Introductionmentioning

confidence: 99%

Wavelet packet analysis of the applied voltage waveform as a monitoring technique of the outdoor insulation surface

Moula

Mekhaldi

Teguar

2013

2013 IEEE International Conference on Solid Dielectrics (ICSD)

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“…The use of leakage current characterization for estimating the condition of the insulators, and hence detecting the dry-band arc discharges has previously been reported [7,8].…”

Section: Introductionmentioning

confidence: 99%

Detection of Corona and Dry-Band Arc Discharges on Nano-Composite Epoxy Insulators Using Rf Sensing

Fernando¹,

Wong²,

Rowe³

2012

PIER

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Abstract-RF radiation due to corona and dry-band arc discharges have been observed using an antenna. Variations in radiated energy were observed due to change in the distance between two water droplets, the contact angle and the volume of the droplets, and the condition of the insulator surface. Changes in the frequency spectrum within the 800 MHz-900 MHz and 1.25 GHz-1.4 GHz frequency bands have been used to identify the transition from corona discharge to dryband arc discharge. The 800 MHz-900 MHz emission band has also been used to monitor the condition of the insulator. These findings highlight the potential for RF sensing in the identification of partial discharges and insulator condition monitoring.

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“…For dynamic signals, it is difficult to achieve strict synchronous sampling even if frequency tracking technologies are adopted [8,9] . When using FFT to estimate signal parameters with asynchronous sampling, estimation error due to the spectral leakage and picket fence effect introduced by the asynchronous sampling and signal cutoff is relatively large [10] .…”

mentioning

confidence: 99%

“…The estimation can provide an information basis for power measurment [2] , fault diagnosis [3] , electrical harmonic compensation [4] , and orthogonal frequency-division multiplexing [5] . Compared with wavelet transforms, the fast Fourier transform (FFT) is more computationally efficient and easier for implementations in embedded systems such as DSP and ARM, and is by now the most widely used in various signal parameter estimation algorithms [6,7] .For dynamic signals, it is difficult to achieve strict synchronous sampling even if frequency tracking technologies are adopted [8,9] . When using FFT to estimate signal parameters with asynchronous sampling, estimation error due to the spectral leakage and picket fence effect introduced by the asynchronous sampling and signal cutoff is relatively large [10] .…”

mentioning

confidence: 99%

Hanning self-convolution window and its application to harmonic analysis

Wen

Teng

Guo

et al. 2009

Sci. China Ser. E-Technol. Sci.

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The Hanning self-convolution window (HSCW) is proposed in this paper. And the phase difference correction algorithm based on the discrete spectrum and the HSCW is given. The HSCW has a low peak side lobe level, a high side lobe roll-off rate, and a simple spectrum representation. Hence, leakage errors and harmonic interferences can be considerably reduced by weighting samples with the HSCW, the parameter estimation by the HSCW-based phase difference correction algorithm is free of solving high order equations, and the overall method can be easily implemented in embedded systems. Simulation and application results show that the HSCW-based phase difference correction algorithm can suppress the impacts of fundamental frequency fluctuation and white noise on harmonic parameter estimation, and the HSCW is advantageous over existing combined cosine windows in terms of harmonic analysis performance.hanning self-convolution window, FFT, phase difference, spectral leakage, frequency fluctuationThe accurate dynamic estimation of signal parameters has been a hot topic in the field of signal processing [1] . The estimation can provide an information basis for power measurment [2] , fault diagnosis [3] , electrical harmonic compensation [4] , and orthogonal frequency-division multiplexing [5] . Compared with wavelet transforms, the fast Fourier transform (FFT) is more computationally efficient and easier for implementations in embedded systems such as DSP and ARM, and is by now the most widely used in various signal parameter estimation algorithms [6,7] .For dynamic signals, it is difficult to achieve strict synchronous sampling even if frequency tracking technologies are adopted [8,9] . When using FFT to estimate signal parameters with asynchronous sampling, estimation error due to the spectral leakage and picket fence effect introduced by the asynchronous sampling and signal cutoff is relatively large [10] . Various kinds of windows, e.g., the rectangular window [11] , the Hanning window [12] , the Hamming window [13] , the Blackman window [14] , the Blackman-Harris window [15] , the RifeVincent window [16] , the Nuttall window [17] , the polynomial windows [18] , the flat-top window [19] , and the rectangular convolution window [20] , have been proposed and used in the windowed interpolation FFT algorithms, and they can in some degree suppress spectral leakage and increase the accuracy of the signal parameter estimation. The use of the FFT algorithms with dual-spectrum-line [7,12,14] or multi-spectrum-line [6,8] interpolation based on high order combined cosine windows in fundamental and harmonics parameter estimation involves, however, solving high order equations, which is computationally expensive [21][22][23] . Different approaches have been proposed to solve the problem. Yang, Ding et al. gave a discrete phase difference correction algorithm suitable for all kinds of symmetrical windows, which can calculate signal parameters without relying on the expression of the window spectral function [24] . Yang et al. proposed ...

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Leakage current characterization for estimating the conditions of non-ceramic insulators’ surfaces

Cited by 27 publications

References 6 publications

Wavelet packet analysis of the applied voltage waveform as a monitoring technique of the outdoor insulation surface

Wavelet packet analysis of the applied voltage waveform as a monitoring technique of the outdoor insulation surface

Detection of Corona and Dry-Band Arc Discharges on Nano-Composite Epoxy Insulators Using Rf Sensing

Hanning self-convolution window and its application to harmonic analysis

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