Name
Title | ||
|---|---|---|
An Integrated Model-Based and Data-Driven Gap Metric Method for Fault Detection and Isolation |
Abstract | ||
|---|---|---|
This article proposes an integrated approach of model-based and data-driven gap metric fault detection and isolation in a stochastic framework. For actuator and sensor faults, an adaptive Kalman filter combining with the generalized likelihood ratio method is suggested. For component faults, especially incipient faults, the model-based scheme maybe not a good choice due to the existence of disturbances or noises. Hence, a novel data-driven gap metric strategy is presented. The design of the appropriate fault cluster center model and radius via the gap metric technique is put forward to enhance the isolability of the incipient faults. Numerical simulation results are given to demonstrate the effectiveness of the proposed fault detection and isolation algorithm. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCYB.2021.3086193 | IEEE Transactions on Cybernetics |
Keywords | DocType | Volume |
Data driven,fault detection and isolation (FDI),gap metric | Journal | 52 |
Issue | ISSN | Citations |
12 | 2168-2267 | 1 |
PageRank | References | Authors |
0.37 | 25 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hailang Jin | 1 | 1 | 0.37 |
| Zhiqiang Zuo | 2 | 334 | 36.94 |
| Yijing Wang | 3 | 34 | 9.28 |
| Lizhen Cui | 4 | 154 | 38.68 |
| Linlin Li 0005 | 5 | 217 | 11.77 |