@inproceedings{74d2e74fa5c64f88991fe3f4f2d3d76f,
title = "Status Assessment Method of Armored Vehicle Engine Oil and Fluid System Based on ARO-SVM",
abstract = "The engine is an important component of armored vehicles, and effective detection of the engine status is an important guarantee for the vehicle and the personnel on board. The lubricating oil information can effectively respond to the health status of the armored vehicle engine, so it is very important to assess the status of the armored vehicle engine. This paper proposes an engine state assessment model based on Artificial Rabbit Optimization Algorithm optimizing Support Vector Machine. The model is simulated and the results show that the algorithm model can effectively assess the engine state and provide a reliable basis for engine maintenance.",
keywords = "Artificial Rabbit Optimization Algorithm, fault diagnosis, lubricating oil system, Support Vector Machine",
author = "Yingshun Li and Ang Yu and Shiming Liu and Xiaojian Yi",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 Prognostics and System Health Management Conference, PHM 2024 ; Conference date: 28-05-2024 Through 31-05-2024",
year = "2024",
doi = "10.1109/PHM61473.2024.00020",
language = "English",
series = "Proceedings - 2024 Prognostics and System Health Management Conference, PHM 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "68--71",
editor = "Ziqiang Pu and Versna Spasic-Jokic and Platon Sovilj and Yifan Wu",
booktitle = "Proceedings - 2024 Prognostics and System Health Management Conference, PHM 2024",
address = "United States",
}