By Topic

Determination of Voltage Level from Electrical Discharge Sound by Probabilistic Neural Network

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)
O. Kalenderli ; Elektrik Mühendisliği Bölümü, İstanbul Teknik Üniversitesi, 34469, Maslak, İstanbul, ; B. Bolat ; S. Bolat

In this study, a different signal recognition approximation is presented to determine applied voltage value using sound records of the electrical discharges (coronas) by a probabilistic neural network. Sound records are obtained experimentally from the electrical discharges at different 50 Hz AC high-voltage levels. Parts of the recording time on the recorded sound has been used to training and test sets of the probabilistic neural network. One of the goals of this work is to determine voltage value from the sound data, and other is optimization of data and diagnostic for less data used and to find correct voltage value. In the algorithmical method, linear prediction coefficients of the different degrees are used. It is shown that the results can be accepted for the work goals

Published in:

2006 IEEE 14th Signal Processing and Communications Applications

Date of Conference:

17-19 April 2006