Use of COTS functional analysis software as an IVHM design tool for detection and isolation of UAV fuel system faults

This paper presents a new approach to the development of
health management solutions which can be applied to both
new and legacy platforms during the conceptual design
phase. The approach involves the qualitative functional
modelling of a system in order to perform an Integrated
Vehicle Health Management (IVHM) design – the
placement of sensors and the diagnostic rules to be used in
interrogating their output. The qualitative functional
analysis was chosen as a route for early assessment of
failures in complex systems. Functional models of system
components are required for capturing the available system
knowledge used during various stages of system and IVHM
design. MADe™ (Maintenance Aware Design
environment), a COTS software tool developed by PHM
Technology, was used for the health management design. A
model has been built incorporating the failure diagrams of
five failure modes for five different components of a UAV
fuel system. Thus an inherent health management solution
for the system and the optimised sensor set solution have
been defined. The automatically generated sensor set
solution also contains a diagnostic rule set, which was
validated on the fuel rig for different operation modes taking
into account the predicted fault detection/isolation and
ambiguity group coefficients. It was concluded that when
using functional modelling, the IVHM design and the actual
system design cannot be done in isolation. The functional
approach requires permanent input from the system designer
and reliability engineers in order to construct a functional
model that will qualitatively represent the real system. In
other words, the physical insight should not be isolated from
the failure phenomena and the diagnostic analysis tools
should be able to adequately capture the experience bases.
This approach has been verified on a laboratory bench top
test rig which can simulate a range of possible fuel system
faults. The rig is fully instrumented in order to allow
benchmarking of various sensing solution for fault
detection/isolation that were identified using functional
analysis.