Lockheed Martin Simulation, Training & Support
ATML on
®
LM-STAR
Michelle Harris
Alicia Helton
407-306-6693
407-306-1592
[email protected]
[email protected]
Steven O’Donnell
407-306-4325
Steven.J.O’[email protected]
Introduction
Lockheed Martin Simulation, Training & Support
Implemented a set of ATML schemas on LM-STAR®
Schemas used –
TestDescription ML (draft 5.0)
TestResults ML (version 0.15)
Diagnostic ML
Bayes
Common Element Model (CEM)
Dynamic Context Model (DCM – version 0.07)
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Lockheed Martin Simulation, Training & Support
Task Definition
Convert a legacy CASS ATLAS TPS into ATML
TestDescription.
Use TestDescription as input to the SELEX TPS Wizard™
and generate TestStand™ sequences.
Execute the TestStand™ sequences on the LM-STAR®.
Collect measured values using ATML TestResults.
Interface with diagnostic reasoner to isolate to the fault
more quickly and more accurately.
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Lockheed Martin Simulation, Training & Support
Initial Approach
Use an externally developed tool to convert ATLAS to
Intermediate XML
Use XML tools to transform the Intermediate XML to
TestDescription
TestDescription will provide the “what” to do information for the
TPS
Use the TPS Wizard™ to generate TestStand™ sequence
files capable of being run on LM-STAR®.
ATLAS
Intermediate
XML
ATML Test
Description
TestStand
Sequence Files
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Issues
Legacy ATLAS TPS was not designed to maximize
portability
Intermediate XML generated from ATLAS was very flat
Difficult to understand test flow and translate into
TestDescription
Legacy ATLAS TPS didn’t adhere to style guide which
would have enforced specific design rules
Multiple fault callout permutations based on data
evaluations made without test numbers created
problems in the diagnostic model development
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Revised Approach
Test
2000
Test Group
1
Next on Fail
DIAGNOSTIC1
Next on Pass
2010
Human intervention verified
the information and added
missing values.
Callout on Fail
A4
High Limit
25
Low Limit
NA
An application was written to
convert the spreadsheet to
TestDescription.
Comparison
EQ
Units
Ohm
Entry Point
No
An application was developed
to extract the “what” to do
information from the ATLAS
and save it to a spreadsheet.
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TestDescription Sample
<Outcomes>
<Outcome ID="0_1" value="Passed"/>
<Outcome ID="0_2" value="Failed"/>
<Outcome ID=" DIAGN1" value="Failed">
<ReplaceComponents>
<ReplaceComponent uutComponentId="UUT-0"/>
</ReplaceComponents>
</Outcome>
<Outcome ID=" DIAGN1" value="Failed">
<ReplaceComponents>
<ReplaceComponent uutComponentId="UUT-1"/>
</ReplaceComponents>
</Outcome>
------snipped---------<Step xsi:type="Step_Test" ID="Step_2" testId="2000">
<Results>
<Result xsi:type="Result_Test" testOutcomeId="2000A">
<NextStep stepId="Step_3"/> <!-- 2020 -->
</Result>
Using the information from TestDescription, the Selex TPS
Wizard™ builds the frame of the new TPS with initiated variables,
test criteria, simulation mode, pre and post conditions, and calls to
“how-to” sequences.
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Lockheed Martin Simulation, Training & Support
TestDescription to LM-STAR®
Needed to create the “how-to” TestStand™ Sequences
Highly intensive manual task
Simplified through the use of Custom Steps
Graphical interface to LM-STAR® system software
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Lockheed Martin Simulation, Training & Support
Diagnostic Model
Description
Model is based off the Bayesian and Common Element Models
from the AI-ESTATE standard
Stored in XML format derived from the AI-ESTATE models
Development of Model
Start with the fault tree of the TPS
Use historical test results and maintenance data to add more
intelligence to the Model
Learning algorithms are used to continuously feed back newly
discovered test results (in TestResults ML format) and
maintenance data
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Lockheed Martin Simulation, Training & Support
Diagnostic Reasoner
Provides run-time environment for using the diagnostic
models
Implements the AI-ESTATE interface to the diagnostic models
Uses the Dynamic Context Model to track session information
Allows for back-tracking through session
Allows restart of Session from previous stopping point
Provides a set of “higher-order” interface functions to minimize
required calls for accessing model/reasoner data
Web-service based interface (using WSDL)
Utilizes a Bayesian Network Analyzer called SMILE
By Decisions System Laboratory – Univ. of Pittsburgh
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Lessons Learned
Lockheed Martin Simulation, Training & Support
Our current process is still heavily dependent on manual
intervention.
Very time-consuming
Current legacy TPSs are implemented with tight coupling making it
difficult to separate the “what” and “how” information
Other ATML schemas such as UUT Description and TestAdapter
could aid in the porting process
They were not mature enough at the time the task started
Would be more cost effective to implement UUT test requirements
on new systems as opposed to re-hosting the application
Not always a one-to-one test mapping from TPS to Diagnostic Model
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Conclusion
Lockheed Martin Simulation, Training & Support
Industry needs tools that can generate and consume
ATML that could be exported to C, ATLAS etc
Using IEEE-1641 for Signal and Test Definition appears
promising and further study by Lockheed Martin is
planned
Lockheed Martin is embracing ATML
TestResults ML is deployed on LM-STAR® systems supporting the
JSF program
As ATML matures, Lockheed Martin is prepared to
implement this technology into our legacy and future
programs
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DEMONTSTRATION
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Lockheed Martin Simulation, Training & Support
Questions
Michelle Harris
407-306-6693
Alicia Helton
407-306-1592
[email protected]
[email protected]
Steven O’Donnell
407-306-4325
Steven.J.O’[email protected]
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