Gas turbine engine condition monitoring using statistical and neural network methods

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Gas turbine engine condition monitoring using statistical and neural network methods

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  • DOI:  10.1049/ic:19961371
  • Location: Leicester, UK
  • Conference date: 18 Sept. 1996
  • Format: PDF
This paper focuses on the two general approaches being investigated for condition monitoring systems: static pattern analysis approach and the dynamical systems approach. In each, statistical and neural network methods are used. The dynamical systems approach lends itself to model-based condition monitoring systems. The performances of the different methods for the monitoring of the complex aircraft gas turbine engine is described, based on real engine data. (6 pages)

Inspec keywords: fault diagnosis; gas turbines; monitoring; neural nets; aerospace engines; nonparametric statistics; closed loop systems; pattern recognition; statistical analysis

Subjects: Other topics in statistics; Pattern recognition; Aerospace engineering computing; Neural computing techniques; Aerospace propulsion; Other topics in statistics; Statistics; Aerospace industry

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