Application of Deep Learning in Comprehensive Performance Evaluation of Aero Engines

Abstract

In view of the high dimension, large noise and large data of aero-engine condition data, combining with the characteristics of deep learning, an aero-engine integrated performance evaluation model is established based on deep learning. The method is validated by the data of 17 JT9D-7R4 engines of an airline. And by comparative with single parameter method, EGT index method and principal component analysis method, this paper reaches the conclusion that deep learning has more advantages of performance evaluation, preventing information loss. It helps the fleet to evaluate the performance of the engine closely, and the result is more creditable.