Name
Title | ||
|---|---|---|
An alternative data-driven fault detection scheme for dynamic processes with deterministic disturbances. |
Abstract | ||
|---|---|---|
This paper proposes an alternative fault detection (FD) scheme, in which the so-called residual signals are generated by means of a projection of process input data. This is the major difference to the existing model-based and data-driven FD schemes, where residual generator is realized based on the process input and output relationship/dynamics. Moreover, this way of residual generation avoids the parameter identification procedure and also allows us to address deterministic disturbances (unknown inputs), which be paid often less attention by data-driven FD methods. In this fashion, the FD issue reduces to detect change of a random matrix. Since it is difficult to directly measure this change, so the trace of a matrix is adopted as the evaluation function. Furthermore, the threshold can be set by considering the boundedness of disturbance. The effectiveness of the proposed method is verified by a simulation study on an inverted pendulum system. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jfranklin.2016.10.031 | Journal of the Franklin Institute |
Field | DocType | Volume |
Residual,Mathematical optimization,Inverted pendulum,Data-driven,Control theory,Fault detection and isolation,Evaluation function,Input/output,Trace (linear algebra),Mathematics,Random matrix | Journal | 354 |
Issue | ISSN | Citations |
1 | 0016-0032 | 6 |
PageRank | References | Authors |
0.59 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwen Chen | 1 | 42 | 12.85 |
| Steven X. Ding | 2 | 1792 | 124.79 |
| Hao Luo | 3 | 297 | 21.40 |
| Kai Zhang | 4 | 71 | 7.38 |