Abstract
This paper describes an end-to-end Integrated
Vehicle Health Management (IVHM) development process
with a strong emphasis on the COTS software tools employed
for the implementation of this process. A mix of physical
simulation and functional failure analysis was chosen as a
route for early assessment of degradation in complex systems
as capturing system failure modes and their symptoms
facilitates the assessment of health management solutions for a
complex asset. The method chosen for the IVHM development
is closely correlated to the generic engineering cycle. The
concepts employed by this method are further demonstrated
on a laboratory fuel system test rig, but they can also be
applied to both new and legacy hi-tech high-value systems.
Another objective of the study is to identify the relations
between the different types of knowledge supporting the health
management development process when using together
physical and functional models. The conclusion of this lead is
that functional modeling and physical simulation should not be
done in isolation. The functional model requires permanent
feedback from a physical system simulator in order to be able
to build a functional model that will accurately represent the
real system. This paper will therefore also describe the steps
required to correctly develop a functional model that will
reflect the physical knowledge inherently known about a given
system.
Vehicle Health Management (IVHM) development process
with a strong emphasis on the COTS software tools employed
for the implementation of this process. A mix of physical
simulation and functional failure analysis was chosen as a
route for early assessment of degradation in complex systems
as capturing system failure modes and their symptoms
facilitates the assessment of health management solutions for a
complex asset. The method chosen for the IVHM development
is closely correlated to the generic engineering cycle. The
concepts employed by this method are further demonstrated
on a laboratory fuel system test rig, but they can also be
applied to both new and legacy hi-tech high-value systems.
Another objective of the study is to identify the relations
between the different types of knowledge supporting the health
management development process when using together
physical and functional models. The conclusion of this lead is
that functional modeling and physical simulation should not be
done in isolation. The functional model requires permanent
feedback from a physical system simulator in order to be able
to build a functional model that will accurately represent the
real system. This paper will therefore also describe the steps
required to correctly develop a functional model that will
reflect the physical knowledge inherently known about a given
system.
Original language | English |
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Number of pages | 16 |
DOIs | |
Publication status | Published - 2013 |
Keywords
- fuels
- valves
- analytical models
- engines
- vehicles
- fault detection