Diagnosis of plant-wide oscillation through data-driven analysis and process understanding

被引:106
|
作者
Thornhill, NF
Cox, JW
Paulonis, MA
机构
[1] UCL, Dept Elect & Elect Engn, London WC1E 7JE, England
[2] Eastman Chem Co, Kingsport, TN 37662 USA
关键词
chemical industry; condition monitoring; control loop performance; fault diagnosis; non-linearity; plant-wide disturbance; power spectrum; process control; surrogate data;
D O I
10.1016/S0967-0661(03)00108-4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Disturbances that propagate throughout a plant due to recycle streams, heat integration or other means can have an especially large impact on product quality and running costs. There is thus a motivation for automated detection of a plant-wide disturbance and for determination of the root cause so that the disturbance may be removed. In this article, data-driven techniques are used to diagnose a plant-wide oscillation in an Eastman Chemical Company plant. A numerical non-linearity index derived from routine measurements was able to suggest the root cause. Process understanding possessed by the plant control engineers then enhanced the data-driven analysis. for instance by identifying a proxy measurement for an unmeasured flow through the valve suspected of being the root cause. In situ tests of just one valve confirmed the suspected root cause and the plant-wide oscillation disappeared after repairing the valve. The diagnosis was right first time and the maintenance effort was thus minimized. The success of the study suggests there exists a fruitful direction for future research in the automated linkage of data-driven analysis with information about the structure and connectivity of the process. (C) 2003 Elsevier Ltd. All rights reserved.
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页码:1481 / 1490
页数:10
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