By Topic

Acoustic-based particle detection in oil using artificial neural networks

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
$31 $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)
Sharkawy, R.M. ; Dept. of Electr. Metrol., Nat. Inst. for Stand., Giza, Egypt ; Anis, H.

This paper contributes to the detection of the presence of free conducting particles in oil-insulated apparatus based on particle-produced acoustics. Acoustic signals are generally produced-under AC-by particle collision against the tank walls. The work uses an inference engine to test for particle contamination in oil by deliberate application of an AC test voltage. The work proposes subjecting the oil-insulated systems to an intentional pre-calculated voltage magnitude for a pre-qualified duration. Using inference, the acoustic signal and pulse train and their statistics could uniquely disclose the characteristics of the contaminating particle

Published in:

Power Tech Proceedings, 2001 IEEE Porto  (Volume:4 )

Date of Conference: