Title :
Sensor fault diagnosis study of UUV based on the grey forecast model
Author :
Li Juan ; Xiaoyou Zhang ; Xinghua Chen ; Mohammed, Naeim Farouk
Author_Institution :
Dept. of Autom., Harbin Eng. Univ., Harbin, China
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 :
autonomous underwater vehicles; fault diagnosis; forecasting theory; grey systems; sensors; UUV system reliability; abnormal sensor model; date sequence gray model; gray model GM(2,1) theory; grey forecast model; sensor fault detection; sensor fault diagnosis; underwater unmanned vehicle system reliability; Compass; Fault detection; Fault diagnosis; Mathematical model; Optical fibers; Predictive models; Robot sensing systems; Fault diagnosis; Gray model; Sensor; Underwater unmanned vehicle;
Conference_Titel :
Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-7097-1
DOI :
10.1109/ICMA.2015.7237750
