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The
Prognostics Framework establishes an object
oriented information framework for system
health monitoring. The information framework
can display or log any relevant information.
CATEGORY
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ELEMENTS
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DESIGN DATA
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Hierarchy
of system, subsystem, parts, faults
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Failure
modes, criticality & rates
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SYSTEM DATA
MANAGEMENT
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Input
Data Definition (format, location,
dimension & description)
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| Prediction
times to be extrapolated in run-time
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| Time
standard
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TEST/SENSOR
DATA
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BIT data
mapping
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| Sensor
data mapping
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| Wear/Usage
data mapping
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HEALTH
MANAGEMENT
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Detection
algorithms
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| Diagnostic
coverage
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| Prediction
algorithms
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| Input
data processing & filtering
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| Confidence
factors
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MISSION
SUPPORT
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Mission
profile
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| Function
correlation to mission phases
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| Function
criticality to mission
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| Immediate
operator actions
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MAINTENANCE
SUPPORT
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Repair
item definition
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| Combinations
of repair items
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| Repair
actions (IETM interface)
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| Parts
ordering data
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| Preventive
Maintenance triggers
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The
object oriented information framework
established by the Prognostics Framework can
be used to integrate any other
equipment-specific prognostic and trending
technique into an overall system-level health
management system. The Prognostic Framework is
capable of integrating other prognostic
techniques that are highly specific to various
equipment classes and failure modes into the
overall framework, such as oil monitoring
systems, vibration analysis systems, thermo graphic/video
imaging, etc.
Integration of prognostic techniques
into the Prognostics Framework is accomplished
by defining the processed results of those
techniques as one (or several) test/sensor
inputs to the model, including fault/symptom
coverage, impact of failures on system
functions and criticality. If the prognostic
technique has its own user interface, the
Prognostics Framework run-time user interface
then has the capability to display that
interface at any time.
The
information architecture used in the
Prognostics Framework is powerful and
flexible. Models for specific pieces of
equipment can be combined into the overall
system hierarchy and test/sensor inferences
and interdependencies across the system level
can be defined.
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