期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 15, 期 5, 页码 2710-2720出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2019.2893125
关键词
Data driven; distributed canonical correlation analysis; fault detection; plant-wide process monitoring
类别
资金
- National Natural Science Foundation of China [61803390, 61773407, 61590921, 61490702, 61703036]
- Foundation for Innovative Research Groups of the National Natural Science Foundation of China [61621062]
- Hunan Provincial Key Laboratory [2017TP1002]
- postdoctoral foundation [2018M643000]
- 111 Project [B17048]
In this paper, a new data-driven fault detection method based on distributed canonical correlation analysis (D-CCA) is proposed to address the plant-wide process monitoring problem. This paper focuses on the distributed plant-wide processes. The core of the proposed method is to reduce uncertainties using correlation information from the neighboring nodes. Furthermore, the cost of the data transmission between network nodes is also reduced by the D-CCA algorithm. When the proposed method and the existing methods are compared using the Tennessee Eastman benchmark process, the false alarm rate, fault detection rate, and the detection delay are comparable. This suggests that the proposed method is feasible.
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