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2012

Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults

7 years 11 months ago
Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults
Many signals of interest are corrupted by faults of an unknown type. We propose an approach that uses Gaussian processes and a general “fault bucket” to capture a priori uncharacterised faults, along with an approximate method for marginalising the potential faultiness of all observations. This gives rise to an efficient, flexible algorithm for the detection and automatic correction of faults. Our method is deployed in the domain of water monitoring and management, where it is able to solve several fault detection, correction, and prediction problems. The method works well despite the fact that the data is plagued with numerous difficulties, including missing observations, multiple discontinuities, nonlinearity and many unanticipated types of fault.
Michael A. Osborne, Roman Garnett, Kevin Swersky,
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where AAAI
Authors Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas
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