Denoising of partial discharge waveforms using multivariate wavelet method

The presence of Partial discharge (PD) in high voltage equipment is an indication of insulation defect or degradation in its insulation. The PD presence can be detected using an electromagnetic sensor, such as fractal sensor. The signals picked-up by the sensor then recorded using a digitizer or an...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2020-05, Vol.857 (1), p.12020
Main Authors: Sinaga, H H, Sitorus, H B H, Permata, D, Yuniati, Y, Vraja, R B
Format: Article
Language:English
Subjects:
Discharge
fractal sensor
Fractals
Insulation
Multivariate analysis
multivariate wavelet
Noise reduction
Partial discharge
Sensors
Signal processing
Waveforms
Wavelet analysis
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Summary:The presence of Partial discharge (PD) in high voltage equipment is an indication of insulation defect or degradation in its insulation. The PD presence can be detected using an electromagnetic sensor, such as fractal sensor. The signals picked-up by the sensor then recorded using a digitizer or an oscilloscope. During the signals pick-up proses, the sensor will capture all the electromagnetic signals around the sensor. Thus, the sensor not only pick-up the PD signals but also unwanted signals or noises. The PD signals captured by the sensor might be buried in heavy noise that the PD signals might be unidentified. To recognize the PD signals de-noising process can be done. In this paper, discussed the denoising process by applying multivariate wavelet to the PD signals captured by using fractal sensor. Results show de-noising process can eliminated noises from PD waveforms even if the PD signals buried by noise signals.
ISSN:1757-8981
1757-899X
1757-899X
DOI:10.1088/1757-899X/857/1/012020