A method for solving the gas path analysis problem of jet engine diagnostics based on a probabilistic approach is presented. The method is materialized through the use of a Bayesian Belief Network (BBN). Building a BBN for gas turbine performance fault diagnosis requires information of a stochastic nature expressing the probability of whether a series of events occurred or not. This information can be extracted by a deterministic model and does not depend on hard to find flight data of different faulty operations of the engine. The diagnostic problem and the overall diagnostic procedure are first described. A detailed description of the way the diagnostic procedure is set-up, with focus on building the BBN from an engine performance model, follows. The case of a turbofan engine is used to evaluate the effectiveness of the method. Several simulated and benchmark fault case scenarios have been considered for this reason. The examined cases demonstrate that the proposed BBN-based diagnostic method composes a powerful tool. This work also shows that building a diagnostic tool, based on information provided by an engine performance model, is feasible and can be efficient as well.
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e-mail: cristo@mail.ntua.gr
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January 2006
Technical Papers
Bayesian Network Approach for Gas Path Fault Diagnosis
C. Romessis,
C. Romessis
Research Assistant
Laboratory of Thermal Turbomachines,
e-mail: cristo@mail.ntua.gr
National Technical University of Athens
, P. O. Box 64069, Athens 15710, Greece
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K. Mathioudakis
K. Mathioudakis
Associate Professor
Laboratory of Thermal Turbomachines,
e-mail: kmathiou@central.ntua.gr
National Technical University of Athens
, P. O. Box 64069, Athens 15710, Greece
Search for other works by this author on:
C. Romessis
Research Assistant
Laboratory of Thermal Turbomachines,
National Technical University of Athens
, P. O. Box 64069, Athens 15710, Greecee-mail: cristo@mail.ntua.gr
K. Mathioudakis
Associate Professor
Laboratory of Thermal Turbomachines,
National Technical University of Athens
, P. O. Box 64069, Athens 15710, Greecee-mail: kmathiou@central.ntua.gr
J. Eng. Gas Turbines Power. Jan 2006, 128(1): 64-72 (9 pages)
Published Online: March 1, 2004
Article history
Received:
October 1, 2003
Revised:
March 1, 2004
Citation
Romessis, C., and Mathioudakis, K. (March 1, 2004). "Bayesian Network Approach for Gas Path Fault Diagnosis." ASME. J. Eng. Gas Turbines Power. January 2006; 128(1): 64–72. https://doi.org/10.1115/1.1924536
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