Fault Prediction Based on Dynamic Model and Grey Time Series Model in Chemical Processes

Fault Prediction Based on Dynamic Model and Grey Time Series Model in Chemical Processes

This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is in-troduced into the grey time series model to predict future trend of measurement value...

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Bibliographic Details
Published in:Chinese journal of chemical engineering Vol. 22; no. 6; pp. 643 - 650
Main Author: 田文德 胡明刚 李传坤
Format: Journal Article
Language:English
Published: Elsevier B.V 01-06-2014
Subjects:
Algorithms
Chemical engineering
Diagnosis
dynamic model
Dynamic models
Fault diagnosis
fault prediction
Faults
grey model
Mathematical models
Time series
time series model
化学过程
化工
历史数据
故障预测
时间序列模型
灰色模型
诊断算法
过程动态模型
time series model
fault prediction
grey model
dynamic model
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Summary:This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is in-troduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to re-trieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.
Bibliography:fault prediction, dynamic model, grey model, time series model
TIAN Wende , HU Minggang ,LI Chuankun （College of Chemical Engineering, Qingdao University of Science ＆ Technology, Qingdao 266042, China 2 Zibo Weichuang Petrochemical Design Co., Ltd, Zibo 255400, China 3 State Key Laboratory of Chemicals Safety, Qingdao Safety Engineering Institute, SINOPEC, Qingdao 266071, China）
11-3270/TQ
This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is in-troduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to re-trieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.
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ISSN:1004-9541
2210-321X
DOI:10.1016/S1004-9541(14)60087-2