Development and Application of a Data-Driven Fault Prediction Method to the Imperial Smelting Furnace Process
In: 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Barcelona, 2009, S. 1174 - 1179
2009Buchaufsatz/Kapitel in Sammelwerk
TechnikFakultät für Ingenieurwissenschaften » Elektrotechnik und Informationstechnik » Automatisierungstechnik und komplexe Systeme
Titel:
Development and Application of a Data-Driven Fault Prediction Method to the Imperial Smelting Furnace Process
Autor*in:
Jiang, Shaohua;Gui, Wei-Hua;Ding, Steven X.UDE
- GND
- 134302427
- LSF ID
- 2347
- ORCID
- 0000-0002-5149-5918
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
Abstract:
This paper addresses the development and application of a data-driven method to the fault diagnosis in imperial smelting furnace (ISF). Based on the method of the weighted least squares vector machines regression, a Hammerstein model is constructed and identified for the ISF. This model is used to predict the dynamic behavior of the furnace and the possible faults in the process. The simulation study shows that the identified model well adapts to the changes in the structural parameters and provides accurate prediction.