Symbolic dynamic analysis of transient time series for fault detection in gas turbine engines

Soumalya Sarkar, Kushal Mukherjee, Soumik Sarkar, Asok Ray

    Research output: Contribution to journalArticle

    17 Scopus citations


    This brief paper presents a symbolic dynamics-based method for detection of incipient faults in gas turbine engines. The underlying algorithms for fault detection and classification are built upon the recently reported work on symbolic dynamic filtering. In particular, Markov model-based analysis of quasi-stationary steady-state time series is extended to analysis of transient time series during takeoff. The algorithms have been validated by simulation on the NASA Commercial Modular Aero Propulsion System Simulation (C-MAPSS) transient test-case generator.

    Original languageEnglish (US)
    Article number014506
    JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
    Issue number1
    Publication statusPublished - Jan 30 2013


    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Information Systems
    • Instrumentation
    • Mechanical Engineering
    • Computer Science Applications

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