CLASSIFICATION OF NEURAL NETWORK FOR TECHNICAL CONDITION OF TURBOFAN ENGINES BASED ON HYBRID ALGORITHM

Abstract

Purpose: This work presents a method of diagnosing the technical condition of turbofan engines using hybrid neural network algorithm based on software developed for the analysis of data obtained in the aircraft life. Methods: allows the engine diagnostics with deep recognition to the structural assembly in the presence of single structural damage components of the engine running and the multifaceted damage. Results: of the optimization of neural network structure to solve the problems of evaluating technical state of the bypass turbofan engine, when used with genetic algorithms.

Authors and Affiliations

Valentin Potapov

Keywords

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  • EP ID EP460960
  • DOI 10.18372/2306-1472.69.11057
  • Views 118
  • Downloads 0

How To Cite

Valentin Potapov (2016). CLASSIFICATION OF NEURAL NETWORK FOR TECHNICAL CONDITION OF TURBOFAN ENGINES BASED ON HYBRID ALGORITHM. Вісник Національного Авіаційного Університету, 69(4), 64-68. https://europub.co.uk./articles/-A-460960