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An extended Tennessee Eastman simulation dataset for fault-detection and decision support systems
Department of Electrical Engineering, Technical University of Denmark, 2800 Kgs., Lyngby, Denmark.
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kgs., Lyngby, Denmark.ORCID iD: 0000-0003-4222-9631
Department of Electrical Engineering, Technical University of Denmark, 2800 Kgs., Lyngby, Denmark.
2021 (English)In: Computers and Chemical Engineering, ISSN 0098-1354, E-ISSN 1873-4375, Vol. 149, article id 107281Article in journal (Refereed) Published
Abstract [en]

The Tennessee Eastman Process (TEP) is a frequently used benchmark in chemical engineering research. An extended simulator, published in 2015, enables a more in-depth investigation of TEP, featuring additional, scalable process disturbances as well as an extended list of variables. Even though the simulator has been used multiple times since its release, the lack of a standardized reference dataset impedes direct comparisons of methods. In this contribution we present an extensive reference dataset, incorporating repeat simulations of healthy and faulty process data, additional measurements and multiple magnitudes for all process disturbances. All six production modes of TEP as well as mode transitions and operating points in a region around the modes are simulated. We further perform fault-detection based on principal component analysis combined with T2 and Q charts using average run length as a performance metric to provide an initial benchmark for statistical process monitoring schemes for the presented data.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 149, article id 107281
Keywords [en]
Tennessee Eastman process, Simulation data, Fault-Detection, Statistical process monitoring, Decision support systems
National Category
Reliability and Maintenance
Research subject
Quality technology and logistics
Identifiers
URN: urn:nbn:se:ltu:diva-85530DOI: 10.1016/j.compchemeng.2021.107281ISI: 000657570600006Scopus ID: 2-s2.0-85110262302OAI: oai:DiVA.org:ltu-85530DiVA, id: diva2:1567937
Note

Validerad;2021;Nivå 2;2021-06-17 (alebob);

Finansiär: Danish Hydrocarbon Research and Technology Centre

Available from: 2021-06-17 Created: 2021-06-17 Last updated: 2021-12-13Bibliographically approved

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Kulahci, Murat

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