Multi-label Fault Classification Experiments in a Chemical Process

The methodology of multi-label classification is experimentally evaluated in the context of a chemical process where the occurrence of multiple faults is a plausible scenario. As a benchmark, the Tennessee Eastman simulator is used. Modifications to the source code of this system were made in order to permit the simultaneous existence of different faulty machine states. In this work, the method of dependent binary relevance is compared to the binary relevance in terms of the subset accuracy performance criterion, since in a complexly coupled chemical process the dependence of certain fault classes should reveal.