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Journal of Control Science and Engineering
Volume 2012, Article ID 478373, 10 pages
Review Article

Progress in Root Cause and Fault Propagation Analysis of Large-Scale Industrial Processes

1Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing 100084, China
2Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2V4

Received 15 September 2011; Revised 17 January 2012; Accepted 1 February 2012

Academic Editor: Onur Toker

Copyright © 2012 Fan Yang and Deyun Xiao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In large-scale industrial processes, a fault can easily propagate between process units due to the interconnections of material and information flows. Thus the problem of fault detection and isolation for these processes is more concerned about the root cause and fault propagation before applying quantitative methods in local models. Process topology and causality, as the key features of the process description, need to be captured from process knowledge and process data. The modelling methods from these two aspects are overviewed in this paper. From process knowledge, structural equation modelling, various causal graphs, rule-based models, and ontological models are summarized. From process data, cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian nets are introduced. Based on these models, inference methods are discussed to find root causes and fault propagation paths under abnormal situations. Some future work is proposed in the end.