An extended Tennessee Eastman simulation dataset for fault-detection and decision support systems. (June 2021) - Reinartz, Christopher; Kulahci, Murat; Ravn, Ole
Highlights: Simulation of 28 process faults at different fault-magnitudes for six operating modes. Simulation of the process' reaction to changes of the control setpoints. Healthy simulation data for other configurations than the original six process modes. Simulation of dynamic transitions between operating modes with different transition times. Performance benchmark for statistical fault-detection schemes for the presented dataset. Abstract: 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 T 2 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.