Abstract
Experimental and industrial case studies are provided to show the usefulness of the previously mentioned connectivity and causality analysis techniques for capturing the direction of information flow and diagnosing the likely rootcause(s) of plant-wide oscillations. For an experimental three-tank system, various methods, including adjacency matrix, Granger causality, transfer entropy, and Bayesian network, are applied to capture the connectivity and causality. For the Eastman process with evident oscillation, the above methods are employed to find the faultpropagation pathways and diagnose the root cause of certain disturbance or fault. For a final tailings pump house process, process data and process knowledge are used to build the process topology and to validate each other. Some suggestions for choosing appropriate methods in practice are also given.
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Yang, F., Duan, P., Shah, S.L., Chen, T. (2014). Case Studies. In: Capturing Connectivity and Causality in Complex Industrial Processes. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-05380-6_6
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DOI: https://doi.org/10.1007/978-3-319-05380-6_6
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-05380-6
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