Name
Abstract | ||
|---|---|---|
The integrity of complex dynamic systems often relies on the ability to detect, during operation, the occurrence of faults, or, in other words, to diagnose the system. The feasibility of this task, also known as diagnosability, depends on the nature of the system dynamics, the impact of faults, and the availability of a suitable set of sensors. Standard techniques for analyzing the diagnosability problem rely on a model of the system and on proving the absence of a faulty trace that cannot be distinguished by a non-faulty one (this pair of traces is called critical pair). |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.artint.2022.103725 | Artificial Intelligence |
Keywords | DocType | Volume |
Diagnosis,Diagnosability,Fair transition systems,Symbolic model-checking | Journal | 309 |
ISSN | Citations | PageRank |
0004-3702 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Bittner | 1 | 30 | 3.67 |
| Marco Bozzano | 2 | 743 | 49.82 |
| Alessandro Cimatti | 3 | 5064 | 323.15 |
| Marco Gario | 4 | 48 | 6.11 |
| Stefano Tonetta | 5 | 573 | 41.61 |
| Viktória Vozárová | 6 | 0 | 0.34 |