An information-theoretic measure for anomaly detection in complex dynamical systems

Abhishek Srivastav, Asok Ray, Shalabh Gupta

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

This paper presents information-theoretic analysis of time-series data to detect slowly evolving anomalies (i.e., deviations from a nominal operating condition) in dynamical systems. A measure for anomaly detection is formulated based on the concepts derived from information theory and statistical thermodynamics. The underlying algorithm is first tested on a low-dimensional complex dynamical system with a known structure-the Duffing oscillator with slowly changing dissipation. Then, the anomaly detection tool is experimentally validated on test specimens of 7075-T6 aluminum alloy under cyclic loading. The results are presented for both cases and the efficacy of the proposed method is thus demonstrated for systems of known and unknown structures.

Original languageEnglish (US)
Pages (from-to)358-371
Number of pages14
JournalMechanical Systems and Signal Processing
Volume23
Issue number2
DOIs
StatePublished - Feb 1 2009

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications

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