By Topic

Advanced suppression of stochastic pulse shaped partial discharge disturbances

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
S. Happe ; Laboratorium fur Hochspannungstechnik, Bergische Univ., Wuppertal, Germany ; H. -G. Kranz ; W. Krause

Digital partial discharge (PD) diagnosis and testing systems are state of the art for performing quality assurance or fault identification on high voltage apparatus as well as commissioning tests. However their on-site application is a rather difficult task as PD information is generally superimposed with electromagnetic disturbances. These disturbances affect negatively all known PD evaluation systems. Especially the detection and suppression of stochastically distributed pulse shaped disturbances is a major problem. To determine such disturbances fast machine intelligent recognition systems are being developed. Three different strategies based on digital signal processing are discussed in this paper, while focusing on time resolved neural signal recognition. The system investigated more closely is currently able to distinguish between PD pulses and disturbances with the disturbances values being ten times higher than the peak values of the PD pulses. Therefore a measuring system acquires the input data in the VHF range (20-100 MHz). The discrimination of the pulses is performed in real time in time domain using fast neural network hardware. With that signal recognition system a noise reassessed phase resolved pulse sequence (PRPS) data set in the CIGRE data format is generated that can be the input source of most PD evaluation software. Optionally a noise reassessed analogue data stream can be generated that is suitable for any conventional PD measuring system.

Published in:

IEEE Transactions on Dielectrics and Electrical Insulation  (Volume:12 ,  Issue: 2 )