Sensor Fault Diagnosis of Aero Engine Control System Based on Honey Badger Optimizer

Yingxue Chen; Linfeng Gou; Huihui Li; Jiayi Wang

doi:10.1016/j.ifacol.2022.05.040

Sensor Fault Diagnosis of Aero Engine Control System Based on Honey Badger Optimizer

Yingxue Chen, Linfeng Gou, Huihui Li, Jiayi Wang

School of Power and Energy

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Abstract

Traditional redundancy detection methods are challenging to achieve fault detection due to high modeling complexity. Aiming at this problem, a data-driven engine sensor fault diagnosis method based on data is established. This paper proposes an intelligent fault diagnosis method based on meta-heuristic optimization, which uses honey badger optimization for feature selection to reduce redundancy information and improve classification accuracy in the problem of aero-engine sensor fault diagnosis. The accuracy of the proposed algorithm is significantly better than the traditional method.

Original language	English
Pages (from-to)	228-233
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	55
Issue number	3
DOIs	https://doi.org/10.1016/j.ifacol.2022.05.040
State	Published - 2022
Event	16th IFAC Symposium on Large Scale Complex Systems: Theory and Applications LSS 2022 - Xi'an, China Duration: 22 Apr 2022 → 24 Apr 2022

Keywords

aero-engine sensor
control system
fault diagnosis
honey badger optimization
meta-heuristic method

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10.1016/j.ifacol.2022.05.040

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title = "Sensor Fault Diagnosis of Aero Engine Control System Based on Honey Badger Optimizer",

abstract = "Traditional redundancy detection methods are challenging to achieve fault detection due to high modeling complexity. Aiming at this problem, a data-driven engine sensor fault diagnosis method based on data is established. This paper proposes an intelligent fault diagnosis method based on meta-heuristic optimization, which uses honey badger optimization for feature selection to reduce redundancy information and improve classification accuracy in the problem of aero-engine sensor fault diagnosis. The accuracy of the proposed algorithm is significantly better than the traditional method.",

keywords = "aero-engine sensor, control system, fault diagnosis, honey badger optimization, meta-heuristic method",

author = "Yingxue Chen and Linfeng Gou and Huihui Li and Jiayi Wang",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.. All rights reserved.; 16th IFAC Symposium on Large Scale Complex Systems: Theory and Applications LSS 2022 ; Conference date: 22-04-2022 Through 24-04-2022",

year = "2022",

doi = "10.1016/j.ifacol.2022.05.040",

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T1 - Sensor Fault Diagnosis of Aero Engine Control System Based on Honey Badger Optimizer

AU - Chen, Yingxue

AU - Gou, Linfeng

AU - Li, Huihui

AU - Wang, Jiayi

PY - 2022

Y1 - 2022

N2 - Traditional redundancy detection methods are challenging to achieve fault detection due to high modeling complexity. Aiming at this problem, a data-driven engine sensor fault diagnosis method based on data is established. This paper proposes an intelligent fault diagnosis method based on meta-heuristic optimization, which uses honey badger optimization for feature selection to reduce redundancy information and improve classification accuracy in the problem of aero-engine sensor fault diagnosis. The accuracy of the proposed algorithm is significantly better than the traditional method.

AB - Traditional redundancy detection methods are challenging to achieve fault detection due to high modeling complexity. Aiming at this problem, a data-driven engine sensor fault diagnosis method based on data is established. This paper proposes an intelligent fault diagnosis method based on meta-heuristic optimization, which uses honey badger optimization for feature selection to reduce redundancy information and improve classification accuracy in the problem of aero-engine sensor fault diagnosis. The accuracy of the proposed algorithm is significantly better than the traditional method.

KW - aero-engine sensor

KW - control system

KW - fault diagnosis

KW - honey badger optimization

KW - meta-heuristic method

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U2 - 10.1016/j.ifacol.2022.05.040

DO - 10.1016/j.ifacol.2022.05.040

M3 - 会议文章

AN - SCOPUS:85134541801

SN - 2405-8963

VL - 55

SP - 228

EP - 233

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 3

T2 - 16th IFAC Symposium on Large Scale Complex Systems: Theory and Applications LSS 2022

Y2 - 22 April 2022 through 24 April 2022

ER -

Sensor Fault Diagnosis of Aero Engine Control System Based on Honey Badger Optimizer

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Keywords

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