Automatic real-time fault detection for industrial assets using metasensors

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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