By Topic

Fuzzy recognition system for power quality events using spline wavelet

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

3 Author(s)
Latha Mercy, E. ; Dept. of Electr. & Electron. Eng., Gov. Coll. of Technol., Coimbatore, India ; Arumugam, S. ; Chandrasekar, S.

In this paper we present a new approach to detect, localize and classify the power quality events. It is a two-stage method in which a spline wavelet transform is used to generate a set of optimal feature vector in the first stage. In second stage, a fuzzy logic-based pattern recognition system is used to classify the various disturbance wave form generated due to power quality violations. The disturbance frequency components are accurately extracted by using spline wavelet. Using this feature power frequency and low frequency disturbances are accurately classified. The instant of occurrence and duration of the power disturbance events are also calculated using spline wavelet.

Published in:

Power Systems Conference and Exposition, 2004. IEEE PES

Date of Conference:

10-13 Oct. 2004