By Topic

Harmonic analysis approach based on wavelet transform and 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
$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

5 Author(s)
Gong Maofa ; Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. &Technol., Qingdao, China ; Liu Xiaocong ; Chai Longqing ; Gong Liming
more authors

The paper presents a new approach based on wavelet and neural network for the estimation of harmonic components in the power system. This proposed method preprocesses the signal using wavelet analysis to get feature extraction of signals. Then it analyses and calculates the feature vector by the artificial neural network (ANN), and the harmonic components of the current can be got. The combination of wavelet and ANN make up for each other's deficiencies and it can solve the frequency aliasing effectively. The structure of this method and the specific algorithm are presented. The simulation model is also built and the results show that the harmonic components can be detected at real time with high precision.

Published in:

Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on

Date of Conference:

6-9 July 2011