Methods for root cause diagnosis of plant-wide oscillations

被引:86
作者
Duan, Ping [1 ]
Chen, Tongwen [1 ]
Shah, Sirish L. [2 ]
Yang, Fan [3 ,4 ]
机构
[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2V4, Canada
[2] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada
[3] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China
[4] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
spectral envelope; root cause diagnosis; plant-wide oscillations; process data analytics; Bayesian networks; causality analysis; SPECTRAL ENVELOPE; TIME-SERIES; NONLINEARITY; COHERENCE; DIMENSION; DELAY;
D O I
10.1002/aic.14391
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Plant-wide oscillations are common in many industrial processes. They may impact the overall process performance and reduce profitability. It is important to detect and diagnose such oscillations. This paper reviews advances in diagnosis of plant-wide oscillations. The main focus of this study is on identifying possible root causes of oscillations using two techniques, one based on data analysis in the temporal and spectral domains and the other based on process connectivity analysis. The process data-based analysis provides an effective way to capture the difference between the root cause variable and the secondary propagated oscillating variables. It is shown that process topology-based methods are capable of finding oscillation propagation pathways and, thus, help in determining the root cause. This paper discusses and compares five such methods-spectral envelope, adjacency matrix, Granger causality, transfer entropy, and Bayesian network inference methods- by application to an industrial benchmark dataset. (c) 2014 American Institute of Chemical Engineers AIChE J, 60: 2019-2034, 2014
引用
收藏
页码:2019 / 2034
页数:16
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