Engine Fault Prediction and Health Evaluation Based on Oil Sensor

被引:2
作者
Li, Yingshun [1 ]
Dong, Wan [2 ]
Yi, Xiaojian [3 ]
Zhang, Yang [4 ]
机构
[1] Dalian Univ Technol, Fac Elect & Elect Engn, Dalian, Peoples R China
[2] Guangxi Univ Sci & Technol, Fac Elect & Elect Engn, Liuzhou, Guangxi, Peoples R China
[3] Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
[4] Shenyang Shunyi Technol Co LTD, Shenyang, Peoples R China
来源
2020 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-BESANCON 2020) | 2020年
基金
中国博士后科学基金;
关键词
fault tree; oil sensor; fault prediction; health evaluation;
D O I
10.1109/PHM-Besancon49106.2020.00044
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In view of the fact that tracked armored vehicles are unable to monitor the indexes such as viscosity, total acid value and pollutant content of engine oil in real time, it is unable to effectively predict the engine failure and evaluate the health status of tracked armored vehicles. In this paper, various physical and chemical indexes in lubricating oil were monitored by oil sensor, engine fault was predicted and the cause of fault was analyzed based on the principle of fault tree. Then, the membership degree of the health status rating was calculated based on the concentration of the monitored abrasive particles, and the comprehensive evaluation system of engine health status was established. The results were analyzed to determine the health status rating. The results of the case show that the oil sensor can monitor and evaluate the engine, and the results are consistent with the actual working conditions, which verifies the rationality of the method.
引用
收藏
页码:223 / 228
页数:6
相关论文
共 15 条
[1]  
Chen C, 2015, THESIS
[2]   Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method [J].
Du, Li ;
Zhu, Xiaoliang ;
Han, Yu ;
Zhao, Liang ;
Zhe, Jiang .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2013, 24 (07)
[3]   A joint time-invariant wavelet transform and kurtosis approach to the improvement of in-line oil debris sensor capability [J].
Fan, X. ;
Liang, M. ;
Yeap, T. .
SMART MATERIALS AND STRUCTURES, 2009, 18 (08)
[4]  
GAO JC, 2015, LUBRICATION SEALING, P89
[5]  
Gao Z., 2017, J GUANGXI U, V42, P409
[6]  
Guo J. M., 2018, EQUIPMENT MACHINERY, P61
[7]  
Jiang Shanging, 2019, Ordnance Industry Automation, V38, P40, DOI 10.7690/bgzdh.2019.04.010
[8]  
Miller JL, 2000, AEROSP CONF PROC, P49, DOI 10.1109/AERO.2000.877882
[9]  
Wang J. X., 2019, SCI TECHNOLOGY WIND, P161
[10]   Condition-Based Maintenance for Power-Shift Steering Transmission Based on Oil Spectral Analysis [J].
Yan Shu-fa ;
Ma Biao ;
Zheng Chang-song .
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39 (11) :3470-3474