期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 63, 期 4, 页码 2606-2614出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2015.2497199
关键词
Fault detection; independent similarity; multimode; process monitoring
资金
- National Natural Science Foundation of China [61325015, 61273163]
In this paper, a new large-scale process monitoring method based on knowledge mining is proposed. The contributions are as follows: 1) between-mode independent similarities are explored to reveal the between-mode relationship for multimode model development and online monitoring; 2) comprehensive subspace decomposition is performed in each mode regarding their relative similarities and influences on process monitoring; 3) each mode is separated into three different systematic subspaces and one residual subspace (RS) based on the between-mode similarities; and 4) different variations are modeled, respectively, for online monitoring to identify mode affiliation and detect the fault status. The proposed method is applied to fault detection of Tennessee Eastman process (TE Process). The monitoring results show the effectiveness of the proposed method, compared to the conventional monitoring method.
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