@inproceedings{0a3a3c20c83d4caa9334a3d6db737c06,
title = "Research on Health Monitoring and Prediction of Aircraft Hydraulic System and Its user systems",
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.",
keywords = "data modeling, health monitoring, health prediction, hydraulic and its user systems",
author = "Yan Liang and Wenyun Yao and Cunbao Ma and Yihan Guo and Qi Ma and Biyuan Hu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021 ; Conference date: 15-10-2021 Through 17-10-2021",
year = "2021",
month = oct,
day = "15",
doi = "10.1109/ITNEC52019.2021.9586946",
language = "英语",
series = "IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1640--1646",
editor = "Bing Xu and Kefen Mou",
booktitle = "IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021",
}