By Topic

Condenser fault diagnosis base on grey multiple attribute fusion

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

4 Author(s)
Xiaojuan Han ; Dept. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China ; Xilin Zhang ; Fangyuan Meng ; Hao Zhang

Grey multiple attribute fusion method is put forward in this paper and applied to condenser fault recognition in which grey relation analysis is combined with multiple attribute decision making. First the state parameters of condenser are fuzzed and use traditional relation analysis method to calculate the relation coefficients between pattern samples and the samples to be diagnosed. The classical domain and joint domain of the fault types are determined by extension interval. The weight value is calculated by proportion coefficient method to be introduced into traditional grey relation index calculation. The best relation index is obtained by optimizing resolution ratio to ensure the stability of relation index space. It is verified that the method provided in this paper can improve the accuracy and reliability of condenser fault recognition by the simulation examples.

Published in:

Automation and Logistics (ICAL), 2011 IEEE International Conference on

Date of Conference:

15-16 Aug. 2011