| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 722342 | IFAC Proceedings Volumes | 2006 | 6 Pages |
Abstract
According to the fault characteristic of the Imperial smelting process (ISP), a novel intelligent integrated fault diagnostic system is developed. Where Fuzzy neural networks are utilized to extracting fault symptom and Expert system is employed for effective fault diagnosis of the process. Furthermore, Fuzzy abductive inference is introduced to diagnose multiple faults. Feasibility of the proposed system is demonstrated through a pilot plant case study.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Weihua Gui, Chunhua Yang, Jing Teng, Wenning Yu,