Name
Title | ||
|---|---|---|
Sensor Selection For Fault Detection And Isolation In Structurally Reconfigurable Systems |
Abstract | ||
|---|---|---|
Fault diagnosis of structurally re-configurable systems is complicated as the system structure changes when the system operates in different modes. It is important that faults can be detected and isolated in each operating mode. In model-based diagnosis, faults are detected and isolated by detecting inconsistencies between model predictions and sensor data. Thus, determining where to mount sensors is an important task to be able to detect and isolate faults, especially when faults can result in unexpected system re-configuration. For structurally re-configurable systems this means selecting a set of sensors that fulfills requirements in multiple models describing the different system modes. A sensor selection algorithm is proposed for structurally re-configurable systems which computes minimal sensor sets that make faults in all modes detectable and isolable. As a case study, the sensor selection algorithm is applied to determine sensor locations in an eight-speed automatic transmission. |
Year | Venue | Field |
|---|---|---|
2018 | 2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | Data modeling,System structure,Fault detection and isolation,Computer science,Control engineering,Real-time computing,Sensor selection,Automatic transmission,Multiple Models |
DocType | ISSN | Citations |
Conference | 0743-1619 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eeshan Deosthale | 1 | 0 | 0.34 |
| daniel jung | 2 | 5 | 3.13 |
| Qadeer Ahmed | 3 | 5 | 7.60 |