Title :
Sensor fault diagnosis for autonomous underwater vehicle
Author :
Chen, Xiaolong ; Xu, Yuru ; Wan, Lei ; Li, Ye
Author_Institution :
State Key Lab. of Autonomous Underwater Vehicle, Harbin Eng. Univ., Harbin, China
Abstract :
To overcome the sensor system problem of fault diagnosis and signal recovery for autonomous underwater vehicle (AUV), a method based on strong tracking filter (STF) theory and singer model of first order time correlation function was proposed. The STF-Singer model by combining the signal processing method and STF method dose not need the accurate mathematical model of the controlled plant, and it has good identification capacity for AUV sensor faults. Computer simulations using experimental data from an AUV sea trail show that the proposed method is effective and feasible.
Keywords :
correlation methods; fault diagnosis; filtering theory; remotely operated vehicles; signal processing; tracking; underwater vehicles; AUV sensor faults; STF singer model; accurate mathematical model; autonomous underwater vehicle; first order time correlation function; sensor fault diagnosis; sensor system problem; signal recovery; strong tracking filter theory; Acceleration; Data models; Equations; Fault diagnosis; Mathematical model; Predictive models; Underwater vehicles; Autonomous underwater vehicle; Fault diagnosis; Singer-model; Strong-tracking filter;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569278
