| Autor: |
Yuchen He, Jiusun Zeng |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 7, Pp 17337-17346 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2895847 |
| Popis: |
For the purpose of monitoring large-scale distributed processes, a double layer fault detection method based on hierarchical multi-block decomposition is proposed. The process variables are first divided into multiple blocks using mutual information-based hierarchical decomposition. The Gaussian and non-Gaussian information in each block are divided into two layers using the partial least squares and a non-Gaussian regression method, respectively. The corresponding monitoring statistics constructed for both the Gaussian and non-Gaussian components are then integrated using the support vector data description. The performance of the proposed method is demonstrated by the application studies to a numerical example and the Tennessee Eastman (TE) benchmark process. The results show that the superiority of the proposed method over conventional methods. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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