Research on Comparison of Different Algorithms in Diagnosing Faults of Aircraft Engines
Author:
Affiliation:
1. COMAC Shanghai Aircraft Customer Service, China
Publisher
FapUNIFESP (SciELO)
Subject
Aerospace Engineering
Link
http://www.scielo.br/pdf/jatm/v13/2175-9146-jatm-13-e3821.pdf
Reference19 articles.
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2. Special Issue on Embedded Sensors for Fault Diagnosis in Electrical Wiring Interconnection Systems, Power Grids, Structural Cables, Pipelines, and Electrical Machines;Furse C;IEEE Sensors Journal,2021
3. Deep quantum inspired neural network with application to aircraft fuel system fault diagnosis;Gao Z;Neurocomputing,2017
4. Engine gearbox fault diagnosis using machine learning approach;Kiran V;J Qual Maint Eng,2018
5. Research Progress on Typical Fault Monitoring and Diagnosis of Aircraft Engine;Li J,2020
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1. Intelligent fault diagnosis methods toward gas turbine: A review;Chinese Journal of Aeronautics;2023-09
2. Fault diagnosis and location of hydraulic system of domestic civil aircraft based on logic data;Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University;2022-08
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