Name
Abstract | ||
|---|---|---|
Fault diagnosis is a crucial and challenging task in the automatic control of complex systems, whose efficiency depends on the diagnosability property of a system. Diagnosability describes the system property allowing one to determine with certainty whether a given fault has effectively occurred based on the available observations. However, this is a quite strong property that generally requires a high number of sensors. Consequently, it is not rare that developing a diagnosable system is too expensive. In this paper, we analyze a new discrete event system property called manifestability, that represents the weakest requirement on observations for having a chance to identify on line fault occurrences and can be verified at design stage. Intuitively, this property makes sure that a faulty system cannot always appear healthy, i.e., has at least one future behavior after fault occurrence observably distinguishable from all normal behaviors. Then, we prove that manifestability is a weaker property than diagnosability before proposing an algorithm with PSPACE complexity to automatically verify both properties. Furthermore, we prove that the problem of manifestability verification itself is PSPACE-complete. The experimental results show the feasibility of our algorithm from a practical point of view. Finally, we compare our approach with related work. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00359-3_8 | VERIFICATION AND EVALUATION OF COMPUTER AND COMMUNICATION SYSTEMS |
DocType | Volume | ISSN |
Conference | 11181 | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lina Ye | 1 | 26 | 8.75 |
| Philippe Dague | 2 | 248 | 28.20 |
| Delphine Longuet | 3 | 0 | 0.34 |
| Laura Brandán Briones | 4 | 75 | 4.99 |
| Agnes Madalinski | 5 | 1 | 1.03 |