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SCIENCE CHINA Information Sciences, Volume 60, Issue 1: 012205(2017) https://doi.org/10.1007/s11432-015-0897-0

Model-based diagnosis of incomplete discrete-event system with rough set theory

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  • ReceivedApr 19, 2016
  • AcceptedMay 23, 2016
  • PublishedNov 23, 2016

Abstract

Fault diagnosis of discrete-event system (DES) is important in the preventing of harmful events in the system. In an ideal situation, the system to be diagnosed is assumed to be complete; however, this assumption is rather restrictive. In this paper, a novel approach, which uses rough set theory as a knowledge extraction tool to deal with diagnosis problems of an incomplete model, is investigated. DESs are presented as information tables and decision tables. Based on the incomplete model and observations, an algorithm called Optimizing Incomplete Model is proposed in this paper in order to obtain the repaired model. Furthermore, a necessary and sufficient condition for a system to be diagnosable is given. In ensuring the diagnosability of a system, we also propose an algorithm to minimize the observable events and reduce the cost of sensor selection.


Acknowledgment

Acknowledgments

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61272208, 61133011, 41172294, 61170092) and Jilin Province Science and Technology Development Plan (Grant No. 201201011).


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