Subspace method aided data-driven design of fault detection and isolation systems
In: Auf meine Merkliste Journal of process control : a journal affiliated with IFAC, the International Federation of Automatic Control, Jg. 19 (2009), Heft 9, S. 1496 - 1510
2009Artikel/Aufsatz in Zeitschrift
TechnikFakultät für Ingenieurwissenschaften » Elektrotechnik und Informationstechnik » Automatisierungstechnik und komplexe Systeme
Titel:
Subspace method aided data-driven design of fault detection and isolation systems
Autor*in:
Ding, Steven X.UDE
- GND
- 134302427
- LSF ID
- 2347
- ORCID
-
0000-0002-5149-5918
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
Erscheinungsjahr:
2009
Erschienen in
Auf meine Merkliste Journal of process control : a journal affiliated with IFAC, the International Federation of Automatic Control
in:
Jg. 19 (2009), Heft 9, S. 1496 - 1510
ISSN
Abstract:
This paper deals with data-driven design of fault detection and isolation (FDI) systems. The basic idea is to identify a primary form of residual generators, instead of the process model, directly from test data and, based on it, to design advanced FDI systems. The proposed method can be applied for the parity space and observer based detection and isolation of sensor and actuator faults as well as the construction of soft-sensors. The application of the proposed method is illustrated by a simulation study on the Tennessee Eastman process.