期刊
JOURNAL OF PROCESS CONTROL
卷 65, 期 -, 页码 107-117出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2017.08.010
关键词
Plant-wide processes; Key performance index; Predictive modeling; Diagnosis; Distributed data modeling
资金
- National Natural Science Foundation of China (NSFC) [61673337]
In this work, a distributed predictive modeling framework is proposed for prediction and diagnosis of key performance indices in plant-wide processes. With block division of the plant-wide process, key data information can be extracted more efficiently, based on which the predictive model can then be developed for regression of the key performance indices. In order to determine the root causes of performance degradation for the key performance index, a diagnostic scheme is developed among this framework. First, the critical blocks are identified through definition of the block contribution in the diagnostic model. The contribution of each process variable is then evaluated inside each critical block, based on which the root causes of performance degradation can be successfully located. An example of the distributed modeling method is realized by using the basic Principal Component Analysis and Gaussian Process Regression models, with a detailed case study on the TE benchmark process. (C) 2017 Published by Elsevier Ltd.
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