Research on Health Monitoring and Prediction of Aircraft Hydraulic System and Its user systems

Yan Liang, Wenyun Yao, Cunbao Ma, Yihan Guo, Qi Ma, Biyuan Hu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aircraft hydraulic system is an important system responsible for capacity transmission, which has a great impact on the safety of aircraft flight mission. Therefore, it is imperative to study the health monitoring and prediction of aircraft hydraulic system and its user systems. In this paper, the hydraulic system and its user systems of a certain type of domestic aircraft are taken as the research object. On the basis of analyzing its working principle and using relevant flight parameters, a health monitoring method of hydraulic system and its user systems based on BP neural network and Support Vector Machine (SVM) algorithm is proposed, thus the health monitoring of the hydraulic system and its user systems of aircraft is realized. Based on health monitoring, Logistic Regression (LR) model and Support Vector Machine Regression (SVR) algorithm are used to predict the change trend of aircraft health mechanism and health state, then the health prediction of aircraft hydraulics and its user systems is realized.

Original languageEnglish
Title of host publicationIEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021
EditorsBing Xu, Kefen Mou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1640-1646
Number of pages7
ISBN (Electronic)9781665415989
DOIs
StatePublished - 15 Oct 2021
Event5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021 - Xi'an, China
Duration: 15 Oct 202117 Oct 2021

Publication series

NameIEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

Conference

Conference5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021
Country/TerritoryChina
CityXi'an
Period15/10/2117/10/21

Keywords

  • data modeling
  • health monitoring
  • health prediction
  • hydraulic and its user systems

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