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

Online Fault Diagnosis of Discrete Event Systems. A Petri Net-Based Approach

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)

This paper is concerned with an online model-based fault diagnosis of discrete event systems. The model of the system is built using the interpreted Petri nets (IPN) formalism. The model includes the normal system states as well as all possible faulty states. Moreover, it assumes the general case when events and states are partially observed. One of the contributions of this work is a bottom-up modeling methodology. It describes the behavior of system elements using the required states variables and assigning a range to each state variable. Then, each state variable is represented by an IPN model, herein named module. Afterwards, using two composition operators over all the modules, a monolithic model for the whole system is derived. It is a very general modeling methodology that avoids tuning phases and the state combinatory found in finite state automata (FSA) approaches. Another contribution is a definition of diagnosability for IPN models built with the above methodology and a structural characterization of this property; polynomial algorithms for checking diagnosability of IPN are proposed, avoiding the reachability analysis of other approaches. The last contribution is a scheme for online diagnosis; it is based on the IPN model of the system and an efficient algorithm to detect and locate the faulty state. Note to Practitioners-The results proposed in this paper allow: 1) building discrete event system models in which faults may arise; 2) testing the diagnosability of the model; and 3) implementing an online diagnoser. The modeling methodology helps to conceive in a natural way the model from the description of the system's components leading to modules that are easily interconnected. The diagnosability test is stated as a linear programming problem which can be straightforward programmed. Finally, the algorithm for online diagnosis leads to an efficient procedure that monitors the system's outputs and handles the normal behavior model. This provides an oppo- rtune detection and location of faults occurring within the system

Published in:

Automation Science and Engineering, IEEE Transactions on  (Volume:4 ,  Issue: 1 )

Date of Publication:

Jan. 2007

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.