Abstract
In this chapter, the process monitoring methods in Part III are compared and contrasted through application to the Tennessee Eastman plant simulator (TEP). The proficiencies of the process monitoring statistics listed in Tables 9.2–9.4 are investigated for fault detection, identification, and diagnosis. The evaluation and comparison of the statistics are based on criteria that quantify the process monitoring performance. To illustrate the strengths and weaknesses of each statistic, Faults 1, 4, 5, and 11 are selected as specific case studies in Sections 10.2, 10.3, 10.4, and 10.5, respectively. Sections 10.6, 10.7, and 10.8 present and apply the quantitative criteria for evaluating the fault detection, identification, and diagnosis statistics, respectively. The overall results of the statistics are evaluated and compared. Results corresponding to the case studies are highlighted in boldface in Tables 10.6 to 10.20.
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© 2000 Springer-Verlag London
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Russell, E.L., Chiang, L.H., Braatz, R.D. (2000). Results and Discussion. In: Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-0409-4_10
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DOI: https://doi.org/10.1007/978-1-4471-0409-4_10
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1133-7
Online ISBN: 978-1-4471-0409-4
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