By Topic

Investigation of a comprehensive identification method used in acoustic detection system for GIS

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

5 Author(s)
W. R. Si ; State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering Xi'an Jiaotong University ; J. H. Li ; D. J. Li ; J. G. Yang
more authors

Nowadays, the acoustic detection is widely used for defect diagnosis of gas insulated substations (GIS) in normal operation and factory tests. In this paper in order to develop a data analyzer for acoustic detection system to make an assistant diagnosis, the characteristic of acoustic signals generated by different artificial defects such as protrusions, floating shield, void in spacer and bouncing particles are investigated. Some meaningful parameters behind the detected acoustic signals are extracted and discussed, which are used to distinguish background noise, partial discharge (PD) phenomena or bouncing particles. Based on those works, a comprehensive identification method realized by processing the acoustic pulse sequences qi, ( Δ ti, qi) and (ti, qi) is introduced, which gives a recognition result with noise, PD type or bouncing particles. For the sequence (ti, qi), the backpropagation artificial neural network optimized by genetic algorithm (GA-BPANN) is used as a classifier based on the fingerprint consisting of 24 operators, which are derivate from typical 2D histograms of phase-resolved partial discharge (PRPD). And with considering the trigger source may having a phase difference from the working voltage, identification with phase compensation (IPC) is used as a try to deal with the challenge. Experimental results show that the comprehensive identification method is practical and effective.

Published in:

IEEE Transactions on Dielectrics and Electrical Insulation  (Volume:17 ,  Issue: 3 )