The Prognostic Method of Engine Gas Path Based-on Convolutional Neural Network

Zhongdong Jiang, Hongzheng Fang, Hui Shi, Shuai Ren, Hao Yang, Fei Wang


In recent years, the development of deep learning methods have brought new ideas to engine prognosis and health management. The failure prediction method based on convolutional neural network is studied, and the software platform of the algorithm for engine gas path fault diagnosis and prognosis is realized. Using the test data from engine simulation, verification study shows that prognostic method proposed has better feasibility and effectiveness for the prognostic technology of aircraft engine compared with other data-driven prediction methods.


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