Systematic process for building a fault diagnoser based on petri nets applied to a helicopter
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2015-09
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Abstract
This work presents a systematic process for building a Fault Diagnoser (FD), based on Petri Nets (PNs) which has been applied
to a small helicopter. This novel tool is able to detect both intermittent and permanent faults. The work carried out is discussed
from theoretical and practical point of view. The procedure begins with a division of the whole system into subsystems, which
are the devices that have to be modeled by using PN, considering both the normal and fault operations. Subsequently, the models
are integrated into a global Petri Net diagnoser (PND) that is able to monitor a whole helicopter and show critical variables to
the operator in order to determine the UAV health, preventing accidents in this manner. A Data Acquisition System (DAQ) has
been designed for collecting data during the flights and feeding PN diagnoser with them. Several real flights (nominal or under
failure) have been carried out to perform the diagnoser setup and verify its performance. A summary of the validation results
obtained during real flight tests is also included. An extensive use of this tool will improve preventive maintenance protocols for
UAVs (especially helicopters) and allow establishing recommendations in regulations.