In this paper the problem of fault diagnosis of the navigation-piloting sensors in autonomous underwater vehicles is considered. The aim consists in developing the sensor fault diagnosis method allowing one to take into account the incipient faults. Fuzzy logic is used for diagnostic decision making.
The autonomous underwater vehicles (AUVs) are complex technical systems which safety and reliable operation deserves particular attention. Navigation-piloting sensors are important components of the AUVs which are necessary to control a motion trajectory. Since malfunctions and faults occurring in these sensors can lead to erroneous mission fulfilment or loss of the vehicle, it is necessary to detect and isolate a faulty sensor early. There are some different methods of fault diagnosis: signal-based, analytical model-based, knowledge-based (Frank, 1990; Frank 1996). To diagnosis the AUVs navigation-piloting sensors, analytical modelbased methods are used that allows one to use the redundancy of the AUV mathematical model. The diagnostic methods based on checking analytical relationships between input and output signals of the AUV are performed. In this paper, to provide the diagnosis process, observer-based methods are used. In this case, the actual AUV sensor measurement is compared with a fault-free observer output signal driven by the control signals and measurements of other sensors of the AUV. Difference between the actual sensor measurement and corresponding observer output signal is a residual signal that carries all possible information about the faults in the system. Diagnosis based on analysis of all residuals values is performed. For diagnosis purposes, the residuals values are evaluated. There are several methods of residual evaluation: threshold logic, statistical decision theory, pattern recognition, fuzzy decision making, or neural networks (Frank, 1996). From incipient fault diagnosis point of view, application of fuzzy logic is of high practical interest.