Name
Abstract | ||
|---|---|---|
This paper presents a novel methodology for the purpose of fault detection and isolation (FDI) to a two-tank system. This new methodology benefits from the basic facts that faults are embedded in the analytical redundancy relations (ARRs) and that the occurrence of a fault will cause the corresponding ARRs to change. Based on these facts, the minimal isolation set as an important concept is introduced to make each fault in the fault set F detectable and isolable. Then, the sensor placement problem consists in determining an optimal minimal isolation set associated with the least number of sensors. A dedicated genetic algorithm is developed to solve the formulated sensor placement problem. A case study of a two-tank system shows that the proposed methodology performs well. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ETFA.2012.6489615 | ETFA |
Keywords | Field | DocType |
tanning,tanks (containers),analytical redundancy relations,fault diagnosis,genetic algorithm,genetic algorithms,optimal minimal isolation,condition monitoring,two tank system,sensor placement | Fault detection and isolation,Control engineering,Redundancy (engineering),Condition monitoring,Engineering,Genetic algorithm | Conference |
ISSN | ISBN | Citations |
1946-0740 E-ISBN : 978-1-4673-4736-5 | 978-1-4673-4736-5 | 0 |
PageRank | References | Authors |
0.34 | 8 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoyi Chi | 1 | 10 | 2.27 |
| Danwei Wang | 2 | 1529 | 175.13 |
| Ming Yu | 3 | 13 | 3.44 |
| Marjan Alavi | 4 | 5 | 0.84 |
| Tung Le | 5 | 37 | 5.87 |
| Ming Luo | 6 | 66 | 5.25 |