Time discretisation applied to anomaly detection in a marine engine

Authors:
Ian Morgan;Honghai Liu;George Turnbull;David Brown
Affiliations:
Institute of Industrial Research, The University of Portsmouth, Portsmouth, England, UK;Institute of Industrial Research, The University of Portsmouth, Portsmouth, England, UK;Institute of Industrial Research, The University of Portsmouth, Portsmouth, England, UK;Institute of Industrial Research, The University of Portsmouth, Portsmouth, England, UK
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Year:
2007

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Abstract

An introduction to the problems associated with anomaly detection in a marine engine, explaining the benefits that the SAX representation brings to the field. Despite limitations in accuracy of the SAX representation in comparison with the normalised time series, we conclude that because of the reduction in data points that should be processed SAX should be considered further as a valid and efficient representation. Finally, a continuation of the work to make the approach more viable in the real world is briefly noted based upon Markov Chaining and Support Vector Machines.