@inproceedings{7df9d3a7ad0641848a2db21bf8c99407,
title = "Sensor fault diagnosis study of UUV based on the grey forecast model",
abstract = "The overall reliability of the underwater unmanned vehicle(UUV) system is improved. This paper mainly study sensor fault diagnosis of UUV. On the basis of analyzing the abnormal sensor model of UUV, put forward the corresponding method of fault diagnosis. The improved gray model GM(2,1) theory is introduced into the fault diagnosis of underwater unmanned vehicle. On the sensor sample date sequence gray model is established. Through analyzing the actual output signal and the output signal of this model, detect sensor fault in real time.",
keywords = "Fault diagnosis, Gray model, Sensor, Underwater unmanned vehicle",
author = "Li Juan and Xiaoyou Zhang and Xinghua Chen and Mohammed, \{Naeim Farouk\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Conference on Mechatronics and Automation, ICMA 2015 ; Conference date: 02-08-2015 Through 05-08-2015",
year = "2015",
month = sep,
day = "2",
doi = "10.1109/ICMA.2015.7237750",
language = "English",
series = "2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1750--1754",
booktitle = "2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015",
address = "United States",
}