Using modern clustering techniques for parametric fault diagnostics of turbofan engines

Using modern clustering techniques for parametric fault diagnostics of turbofan engines

The 21st century aviation and aerospace technologies have evolved and become more complex and technical. Turbofan jet engines as well as their cousins, the rocket engines (liquid/solid) have gone through several design upgrades and enhancements during the course of their design and exploitation. The...

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Bibliographic Details
Main Author: I. J. Buraimah
Format: Article
Language:Russian
Published: Moscow State Technical University of Civil Aviation 2020-12-01
Series:Научный вестник МГТУ ГА
Subjects:
engine fault diagnostics
parametric data
turbofan jet engines
monitoring
in-flight data handling
neural network
cmeans
k-means
dbscan
clustering analysis
cluster pattern
clustering techniques
algorithm
flight parameters
exhaust gas temperature
data analysis
self-organizing maps
Online Access:https://avia.mstuca.ru/jour/article/view/1763

Internet

https://avia.mstuca.ru/jour/article/view/1763

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