Fault Detection and Control Systems
This cluster of papers focuses on the application of various data-driven and statistical techniques for process fault detection and diagnosis in industrial settings. It covers topics such as process monitoring, fault isolation, soft sensors, model-based diagnosis, and the use of machine learning in analyzing and improving industrial processes.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.