Evaluation Method of Aero-engine Performance Based on Hybrid AP-HMM Model

Yin Cui; Liling Ma

doi:10.1049/icp.2021.0467

Evaluation Method of Aero-engine Performance Based on Hybrid AP-HMM Model

Yin Cui, Liling Ma^*

^*Corresponding author for this work

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

As the aero-engine is the heart of aircraft, it is very important to monitor and diagnose the performance of the aero-engine effectively. In this paper, a method based on AP(Affinity Propagation) clustering HMM(Hidden Markov Model) model is proposed to evaluate the aero-engine performance. First, the correlation analysis method is used to extract the main attributes of the original data. Then, AP theory and K-NN are used for clustering with different performances to establish the HMM model for performance analysis. The experimental results show that this method has good effect on the performance analysis of aero-engine, which can improve the clustering effect, the classification accuracy of boundary sampling points and the accuracy of performance evaluation results.

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	903-907
Number of pages	5
Volume	2020
Edition	3
ISBN (Electronic)	9781839534195
DOIs	https://doi.org/10.1049/icp.2021.0467
Publication status	Published - 2020
Event	2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020 - Virtual, Online Duration: 18 Sept 2020 → 21 Sept 2020

Conference

Conference	2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020
City	Virtual, Online
Period	18/09/20 → 21/09/20

Keywords

AP clustering
Aero-engine
HMM model
classification accuracy
performance evaluation

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10.1049/icp.2021.0467

Cite this

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title = "Evaluation Method of Aero-engine Performance Based on Hybrid AP-HMM Model",

abstract = "As the aero-engine is the heart of aircraft, it is very important to monitor and diagnose the performance of the aero-engine effectively. In this paper, a method based on AP(Affinity Propagation) clustering HMM(Hidden Markov Model) model is proposed to evaluate the aero-engine performance. First, the correlation analysis method is used to extract the main attributes of the original data. Then, AP theory and K-NN are used for clustering with different performances to establish the HMM model for performance analysis. The experimental results show that this method has good effect on the performance analysis of aero-engine, which can improve the clustering effect, the classification accuracy of boundary sampling points and the accuracy of performance evaluation results.",

keywords = "AP clustering, Aero-engine, HMM model, classification accuracy, performance evaluation",

author = "Yin Cui and Liling Ma",

note = "Publisher Copyright: {\textcopyright} 2020 The Institution of Engineering and Technology.; 2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020 ; Conference date: 18-09-2020 Through 21-09-2020",

year = "2020",

doi = "10.1049/icp.2021.0467",

language = "English",

volume = "2020",

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booktitle = "IET Conference Proceedings",

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TY - GEN

T1 - Evaluation Method of Aero-engine Performance Based on Hybrid AP-HMM Model

AU - Cui, Yin

AU - Ma, Liling

PY - 2020

Y1 - 2020

N2 - As the aero-engine is the heart of aircraft, it is very important to monitor and diagnose the performance of the aero-engine effectively. In this paper, a method based on AP(Affinity Propagation) clustering HMM(Hidden Markov Model) model is proposed to evaluate the aero-engine performance. First, the correlation analysis method is used to extract the main attributes of the original data. Then, AP theory and K-NN are used for clustering with different performances to establish the HMM model for performance analysis. The experimental results show that this method has good effect on the performance analysis of aero-engine, which can improve the clustering effect, the classification accuracy of boundary sampling points and the accuracy of performance evaluation results.

AB - As the aero-engine is the heart of aircraft, it is very important to monitor and diagnose the performance of the aero-engine effectively. In this paper, a method based on AP(Affinity Propagation) clustering HMM(Hidden Markov Model) model is proposed to evaluate the aero-engine performance. First, the correlation analysis method is used to extract the main attributes of the original data. Then, AP theory and K-NN are used for clustering with different performances to establish the HMM model for performance analysis. The experimental results show that this method has good effect on the performance analysis of aero-engine, which can improve the clustering effect, the classification accuracy of boundary sampling points and the accuracy of performance evaluation results.

KW - AP clustering

KW - Aero-engine

KW - HMM model

KW - classification accuracy

KW - performance evaluation

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U2 - 10.1049/icp.2021.0467

DO - 10.1049/icp.2021.0467

M3 - Conference contribution

AN - SCOPUS:85174649286

VL - 2020

SP - 903

EP - 907

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 2020 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2020

Y2 - 18 September 2020 through 21 September 2020

ER -

Evaluation Method of Aero-engine Performance Based on Hybrid AP-HMM Model

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