Research on aero-engine fault diagnosis based on integrated neural network-Reference-Cited by-同舟云学术

Research on aero-engine fault diagnosis based on integrated neural network

Published:2019-06-30 Issue:2 Volume:5 Page:41-47
ISSN:2351-5279
Container-title:Mathematical Models in Engineering
language:
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Author:

Xiangyang Shi

Publisher

JVE International Ltd.

Subject

General Engineering

Link

https://www.jvejournals.com/article/20636/pdf

Reference8 articles.

1. Wan Peng Research and Implementation of Flight Control Ground Fault Diagnosis System Based on Symptom Analysis. Ph.D. Thesis, University of Electronic Science and Technology, Chengdu, 2018.

2. Research on fault diagnosis of B737 aircraft electric starting system based on BP neural network;Shi;Journal of Binzhou University,2018

3. Ling Yiqin Research on Fault Diagnosis Technology of Aircraft System Based on Fault Propagation Mechanism and Petri Net. Ph.D. Thesis, Nanjing University of Aeronautics and Astronautics, Nanjing, 2017.

4. Hao Yichuan Research on Fault Diagnosis Method of Aircraft Electronic System Based on Rough Set and Neural Network. Ph.D. Thesis, China Civil Aviation University, Tianjin, 2015.

5. Wang Hongwei Research on Key Technologies of Fault Diagnosis and Prediction for Rolling Bearing of Aero-engine. Ph.D. Thesis, Nanjing University of Aeronautics and Astronautics, Nanjing, 2015.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Fault-Tolerant Soft/Hard Hybrid Control for Fault Diagnosis of Aero-engine Sensors;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

2. Aero Engine Gas-Path Fault Diagnose Based on Multimodal Deep Neural Networks;Wireless Communications and Mobile Computing;2020-10-03