Fault Diagnosis of Underwater Vehicle with Neural Network
In order to aim at the character that the uncertainties of the complex system of underwater vehicle (UV) result in model the system very difficult, a wavelet neural network (WNN) is proposed to construct the motion model of UV. The adjustment of the scale factor and shift factor of wavelet and weights of WNN is discussed. The WNN has the ability not only to approach the whole figure of a function but also to catch detail changes of the function, which makes the approaching effect wonderful. Residuals are achieved by comparing the output of WNN with the sensor output. Fault detection rules are distilled from the residuals to execute thruster fault diagnosis. The feasibility of the method presented is verified by simulation experiment results.
fault diagnosis underwater vehicle (UV) thruster fault wavelet neural network (WNN)
Wang Jian-guo
China Ship Development and Design Center, Wuhan 430064
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
1625-1629
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）