Butters, T D and Güttel, S and Shapiro, J L and Sharpe, T J (2015) Automatic real-time fault detection for industrial assets using metasensors. [MIMS Preprint]
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Abstract
Large-scale industrial plants require physical sensors to continuously measure quantities such as temperatures or pressures. A large number of sensors is required to accurately describe the operating state of the plant, which unfortunately makes it very difficult for them to be effectively monitored by human operators. In this work we present a method to construct so-called metasensors, virtual sensors that compress the information from several sensors in an optimal manner. These metasensors are used as inputs to a novel anomaly detection system that automatically alerts operators to abnormal operation behaviour.
| Item Type: | MIMS Preprint |
|---|---|
| Additional Information: | For presentation at the 2015 Asset Management Conference, The Institute of Engineering and Technology, London. |
| Uncontrolled Keywords: | Metasensor, Condition Monitoring, Preventative Action, Asset Management |
| Subjects: | MSC 2010, the AMS's Mathematics Subject Classification > 62 Statistics MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis |
| Depositing User: | Stefan Güttel |
| Date Deposited: | 15 Sep 2015 |
| Last Modified: | 08 Nov 2017 18:18 |
| URI: | https://eprints.maths.manchester.ac.uk/id/eprint/2382 |
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