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Evolution strategy for gas-turbine fault-diagnoses

Author

Listed:
  • Ogaji, S.O.T.
  • Sampath, S.
  • Marinai, L.
  • Singh, R.
  • Probert, S.D.

Abstract

The aim of this investigation is to be able to diagnose gas-path faults in gas turbines by minimising the differences between the observed and simulated data for the engine's behaviour. The simulated data are generated using a known set of faults as the input to the engine-behaviour aero-thermo model and an appropriate objective function is minimised to yield the best solution to the problem. The application of evolution strategy (ES) in the search for this minimum is an effective, flexible, robust and reliable way of solving engine-diagnostics problems. Adopting this approach leads to a considerable reduction in the overall time taken to obtain a convergent solution when compared with that required using a simple genetic-based algorithm.

Suggested Citation

  • Ogaji, S.O.T. & Sampath, S. & Marinai, L. & Singh, R. & Probert, S.D., 2005. "Evolution strategy for gas-turbine fault-diagnoses," Applied Energy, Elsevier, vol. 81(2), pages 222-230, June.
    • Handle: RePEc:eee:appene:v:81:y:2005:i:2:p:222-230
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