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Anomaly Detection in a Multi-engine Aircraft

  • Dinkar Mylaraswamy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)

Abstract

This paper describes an anomaly detection algorithm by monitoring the spin-down of jet engines. The speed profile from multiple engines in an aircraft is cast as a singular value monitoring problem. This relatively simple algorithm is an excellent example of onboard, lightweight feature extractor, the results of which can feed more elaborate trouble shooting procedures. The effectiveness of the algorithm is demonstrated using aircraft data from one of Honeywell’s airline customers.

Keywords

Singular Value Decomposition Fault Diagnosis Anomaly Detection Frictional Loss ASME Turbo Expo 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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    Mathioudakis, K., Kamboukos, P., Stamatis, A.: A turbofan performance deterioration tracking using nonlinear models and optimization. In: ASME Turbo Expo, Amsterdam, The Netherlands (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Dinkar Mylaraswamy
    • 1
  1. 1.Honeywell LaboratoriesMinneapolisUSA

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