Proceedings of the 2016 International Conference on Engineering Management (Iconf-EM 2016)

Research on Fault Diagnosis Method of Aircraft Engine on Basis of Data Classification Prediction

Authors
Jiangwei Hao, Bin Lu
Corresponding Author
Jiangwei Hao
Available Online January 2017.
DOI
https://doi.org/10.2991/iconfem-16.2016.24How to use a DOI?
Keywords
Neural Network;Random Forest; Aircraft Engine Fault Diagnosis
Abstract
.In this article, we introduced the classification and prediction algorithm of data mining into aircraft engine fault diagnosis, then analysis and compare the Random Forest algorithm and Neural Network algorithm.The simulation of these algorithms and experimental results show that the two methods have their own advantages and disadvantages. Combining both of them into system that fault types and potential problems of engines can be found more accurately.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Engineering Management (Iconf-EM 2016)
Part of series
Advances in Economics, Business and Management Research
Publication Date
January 2017
ISBN
978-94-6252-280-0
ISSN
2352-5428
DOI
https://doi.org/10.2991/iconfem-16.2016.24How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jiangwei Hao
AU  - Bin Lu
PY  - 2017/01
DA  - 2017/01
TI  - Research on Fault Diagnosis Method of Aircraft Engine on Basis of Data Classification Prediction
BT  - 2016 International Conference on Engineering Management (Iconf-EM 2016)
PB  - Atlantis Press
SN  - 2352-5428
UR  - https://doi.org/10.2991/iconfem-16.2016.24
DO  - https://doi.org/10.2991/iconfem-16.2016.24
ID  - Hao2017/01
ER  -