Publication Type : Conference Paper
Publisher : 2017 International Conference on Smart grids, Power and Advanced Control Engineering
Source : 2017 International Conference on Smart grids, Power and Advanced Control Engineering (ICSPACE) (2017)
Url : https://ieeexplore.ieee.org/document/8343442
Campus : Bengaluru
School : School of Engineering
Center : Wind Energy Center
Department : Electrical and Electronics
Year : 2017
Abstract : The pre-processing of the Partial Discharge (PD) signal is very important and crucial stage in analyzing condition of the electrical insulation. The PD information is lost in the presence of various noises. The wavelet based adaptive Thresholding de-noising techniques are well suited for reducing the noise. This paper considers the various adaptive thresholding techniques such as Heursure, Minimaxi, VisuShrink, SureShrink, thresholding methods for denoising of the PD signals obtained in various insulation samples using the experimental setup. The PD pulses produced by the insulation samples were detected in the form of discharges through the impedance and is fed through a cable to the PD detector along with a amplitude modulating signal. The developed Wavelet Transform based adaptive thresholding algorithm suitably removes the interferences from the measured PD signals. The performance indices are evaluated which justifies the strength of the algorithm in denoising of experimental PD data.
Cite this Research Publication : S. Madhu, S. Sumathi, and Vidya H. A., “Preprocessing of experimental partial discharge signalsin insulation samples using adaptive signal processing”, in 2017 International Conference on Smart grids, Power and Advanced Control Engineering (ICSPACE), 2017.