Sensor Fault Diagnosis in Autonomous Underwater Vehicle Based on Fuzzy Logic
A0055Anton M. Pisarets Far Eastern State Technical University
A0056Alexey N. Zhirabok Far Eastern State Technical University
The problem of ensuring safety and reliability operation of AUV is
very important. Since malfunctions and faults occurring in the AUV
systems can lead to erroneous mission fulfilment or losses of a
vehicle, it is necessary to give much attention to solution this
Navigation-piloting sensors such as the meters of trim and course, the
meters of angular velocities, the meters of velocity and depth are
important components of the AUV system from which its reliable
operation depends on. Thus the task of early fault detection and
isolation in this sensors are important.
Among different methods of dynamic systems diagnosis using analytical
redundancy model-based methods well established in practice. To
describe dynamic behaviour of the AUV, differential equations are used.
To provide diagnosis process, observer-based methods are used. The i-
th observer is driven by the AUV control signals and sensors output
signals but the i-th one. The difference between the i-th sensor
measurement and corresponding observer output signal is a residual
which is equal to almost null in the normal AUV operating and not null
when a fault occurs. This residual is sensitive to faults of those
sensors which measurements use for its obtaining. Diagnosis based on
analysis of all residuals values is performed.
In the simplest case, for fault detection and isolation, the residual
value is compared with certain threshold. If it is more than this
threshold, it is concluded that the fault occurs in some sensor. Use
of the threshold allows one to find sudden faults (i.e. step-like
changes in the sensors), but this method has small sensitivity to
incipient (slowly developing)faults which is a characteristic property
of the majority of sensors.
To increase the efficiency of the diagnosis process, it is offered to
use the fuzzy logic. In this case, the residual is evaluated as
"small ", "medium ", "big ", etc which reflects a human notion about
residual size. Mathematically, this evaluation is performed using so-
called membership functions. The correspondences of the residual
values to these functions are assigned by the membership grades which
are numbers from interval [0, 1]. These membership grades are used
for faulty sensor isolation. This diagnosis process allows one to
evaluate technical state of the AUV sensors more precise in comparison
with the threshold test.