Fault Detection and Control Systems
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Scope of this subject
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.
OpenAlex generated this cluster description with an LLM. It describes research grouping, not verified findings.
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Research vocabulary
process monitoring; fault-tolerant control; fault detection and isolation; soft sensors; fault isolation; Tennessee Eastman process; industrial process monitoring; sensor faults; actuator faults; residual generation; sensor fault detection; fault detection and diagnosis; fault estimation; chemical process monitoring; multivariate statistical process control; model-based fault detection; unknown input observer; soft sensing; real-time fault detection; data reconciliation; real-time fault diagnosis; sensor fault diagnosis; model-based fault diagnosis; robust fault detection; analytical redundancy
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Local answer status
No owner-reviewed answer has been published for this exact subject page. This is a gap in this collection; it does not establish that the answer is unavailable elsewhere.
Numeric address and provenance
Morton address: 36240454224629365 · morton4x16-v1
Coordinates: (3, 22, 2207, 10876). The address interleaves categorical identifier bits. Nearby addresses are not guaranteed to describe semantically similar subjects.
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