Cart (Loading....) | Create Account
Close category search window

Fault diagnosis model for coking system based on multi-agent

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)
Yi'nan Guo ; College of Information and Electrical Engineering, China University of Mining and Technology ; Dunwei Gong ; Jian Cheng ; Xijin Guo

Aiming at the requirement on complexity, security and timeliness for fault diagnosis of coking process, the multi-agent fault diagnosis model for coking system was proposed by the hiberarchy analysis on coking system fault. Fuzzy relationship matrix knowledge model, learning mechanism based on genetic algorithm and fuzzy diagnosis reasoning process were discussed as an example of coking heating system fault diagnosis. It was validated through actual data that the model can diagnose fault efficiently and exactly and it can fulfill the requirement of production.

Published in:

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on  (Volume:2 )

Date of Conference:

15-19 June 2004

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.