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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yingwei Zhang Tianyou Chai Zhiming Li Chunyu Yang |
| Copyright Year | 2012 |
| Abstract | In this paper, a new online monitoring approach is proposed for handling the dynamic problem in industrial batch processes. Compared to conventional methods, its contributions are as follows: (1) multimodes are separated correctly since the cross-mode correlations are considered and the common information is extracted; (2) the expensive computing load is avoided since only the specific information is calculated when a mode is monitored online; and (3) after that, two different subspaces are separated, and the common and specific subspace models are built and analyzed, respectively. The monitoring is carried out in the subspace. The corresponding confidence regions are constructed according to their respective models. |
| Page Count | 8 |
| File Size | 572281 |
| Starting Page | 277 |
| Ending Page | 284 |
| File Format | |
| ISSN | 2162237X |
| Volume Number | 23 |
| Issue Number | 2 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Monitoring Correlation Vectors Principal component analysis Systematics Furnaces Batch production systems subspace separation Common and specific correlations industrial processes multimode process monitoring |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Computer Networks and Communications Computer Science Applications Software |
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