Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

Notice of Retraction
A Distributed Fault Diagnosis Approach in Power System Based on Fuzzy Reasoning Petri Net

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)
Yang Jian-wei ; Sch. of Electr. Eng., Southwest Jiaotong Univ. Chengdu, Chengdu, China ; He Zheng-you ; Tan Xi-jing ; Zeng Qing-feng

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting

There are some problems in fuzzy Petri net (FPN) applied to complex power systems fault diagnosis, inconformity parallel reasoning, dimension number of incidence matrix is too large, etc. So a distributed power system fault diagnosis based on fuzzy reasoning petri net is proposed, with much better flexibility and applicability, and give the fuzzy reasoning algorithm based on the representation formalism of max-algebra matrix operator. The method can reduce dimension number of incidence matrix and calculation, get all system state values after reasoning, and according to distributed fault diagnosis combined with fuzzy Petri net theory and its ability in describe concurrent system. It can get correct results from simple fault samples, complex fault samples or multiple faults samples simulation experiments, shows better fault tolerance, simple reasoning, fast fault diagnosis and so on, and it is an effective power system fault diagnosis method.

Published in:

Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific

Date of Conference:

28-31 March 2010