By Topic

Partial discharge recognition based on pulse waveform using time domain data compression method

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

2 Author(s)
Zheng Zhong ; Tsinghua Univ., Beijing, China ; Tan Kexiong

A digital integrated system is developed to record partial discharge (PD) pulses and to recognize their patterns by waveforms. Special considerations on the experiment circuit are given to electromagnetic shielding, system bandwidth and pattern variety. Both typical laboratory models and simulation models of stator windings are tested, which represent corresponding PD types in air, transformer oil, artificial cavity of stator bar insulation and along the surfaces of the end-winding. The waveforms of discharge current of distinct models are recorded and their respective features are extracted by segmented time domain data compression method. An artificial neural network is applied to recognize different patterns. Several factors concerning recognition rate are discussed. The training and testing result shows the potentiality of applying waveform analysis in partial discharge recognition

Published in:

Properties and Applications of Dielectric Materials, 2000. Proceedings of the 6th International Conference on  (Volume:1 )

Date of Conference:

2000