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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Valle, S. Qin, S.J. Piovoso, M.J. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Chem. Eng., Texas Univ., Austin, TX, USA (Valle, S.) |
| Abstract | Although fault detection has been well studied in process monitoring under stationary conditions, the identification of faults in chemical processes is a difficult task. We present a new approach in the use of a fault identification index to identify faults based on fault directions extracted from abnormal data using singular value decomposition. The proposed method is demonstrated on an industrial polyester film process which is characterized by frequent set-point changes and multiple grade changes. Further, a comparison between the fault identification index and the contribution plot method is given. |
| Sponsorship | American Autom. Control Council |
| Starting Page | 4466 |
| Ending Page | 4471 |
| File Size | 475500 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780364953 |
| ISSN | 07431619 |
| DOI | 10.1109/ACC.2001.945682 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-06-25 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | Fault diagnosis Fault detection Chemical processes Data mining Principal component analysis Process control Monitoring Singular value decomposition Chemical sensors Data analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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