Grid-based on-line
aeroengine diagnostics
Jim Austin, University of York
Aims
• To build a distributed, Grid based, diagnostic
maintenance system
• To prove the technology on a Rolls Royce
Aeroengine diagnostic maintenance problem
• Demonstrate the process of building a Grid based
system
• To deliver grid-enabled technologies that underpin
the application
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The Application
• The support of engine diagnostics on a
global scale.
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Engine flight data
London Airport
Airline
office
New York Airport
Grid
Maintenance Centre
American data center
European data center
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Aircraft
Engine
Outline architecture
Quote
Systems
Diagnostic
operator
Engine data
Engine data
log
AURA
data search
Operational
Report
Model-based
Interpretation
Maintenance
operator
Database of
Operational
data
Case-based
Reasoning
Decisionsupport
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Example use case
Local Environment
Perform
Extended
Analysis
<<extend>>
Diagnosis /
Prognosis
<<include
Data
Engine
Decision
Support
Perform
Analysis
<<extend>>
<<extend>>
Pattern Match
Status /
Parameters
Modeller
Update
Operation
Provide Domain
Expert
Assessment
Update Local
Diagnostics
Diagnosis
Assessment
Inform Domain
Expert of
Undetected Problem
Domain
Expert /
Maintenance
Planner
Results
Reports
Results
Store Result of
Diagnosis and
Operation
Provide
Statistics
Report
Maintenance
Team
6
Challenges
• Support on-line diagnostics in real time
• Deal with the data from 100,000 engines in
operation
• Prove pattern matching methodology
• Prove the business case for the technology
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Technologies
• AURA: High performance search
technology
• QUOTE: On-engine diagnostics system
• Globus: Grid software
• WR Grid: Demonstrator hardware
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AURA
• High performance ‘search engine’
• Based on neural networks
• Develop for distributed operation
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QUOTE
•
•
•
•
On-engine health assessment
Under trials on Trent 500 now
Will identify novelty
Some diagnostics
10
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White Rose
Computational Infrastructure
Oxford
Super
Janet
Leeds Cluster
Leeds Shared
Memory
White Rose Computational Grid
Sheffield
Distributed Memory
York Shared
Memory
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Our developing architecture
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Industry Collaborators
• DS&S : Rolls Royce data services providers
• Rolls Royce : Data and problem
• WRCG: Esteem, Sun and Streamline:
Demonstrator Grid
• Cybula: AURA technology support
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Academic team
• Austin – project management, data
management
• Tarassenko, Austin – algorithms for fault
identification
• Dew, Djemame – system architecture
• Fleming, Thompson – decision support
• McKay – data modeling
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Academic Team
• McDermid – Dependability
• Wellings – Real time issues
Researchers - 15, including...
• Tom Jackson - Coordinator
• Martyn Fletcher - Software Manager
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End
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