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Decision Support Tools CBR & Modeling

Decision Support Tools CBR & Modeling. Jeff Allan University of Sheffield. DAME: Technology Pull. Rolls-Royce build competitive gas turbine engines: Ever more reliable Greener Quieter DS&S provide effective and efficient after market services:

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Decision Support Tools CBR & Modeling

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  1. Decision Support ToolsCBR & Modeling Jeff Allan University of Sheffield

  2. DAME: Technology Pull • Rolls-Royce build competitive gas turbine engines: • Ever more reliable • Greener • Quieter • DS&S provide effective and efficient after market services: • On time every time, 24hours a day, 7 days a week • Need to understand GT engine behaviour/performance • Predict, diagnose & inform

  3. Engineering Trends • Tools change but the inherent nature of collaboration to achieve business objectives doesn’t! • a car • a gas turbine engine • Technology integration: • active suspension • more electric gas turbines • Knowledge increasingly the value added.

  4. DAME: Sheffield Challenge • Challenge 1 • Provide a means to enable our specialist tools, techniques, and expertise into the collaborative domain: • MOGA • Engine Modelling & FDI • Intelligent Systems Approaches, e.g. CBR • Challenge 2 • To provide a framework to capture process knowledge and enable decision support: • Fault Ranking Tool • Workflow Advisor

  5. An Engine Simulation Grid Service for DAME Xiaoxu Ren Rolls-Royce UTC in Control and Systems Engineering Department of Automatic Control and Systems Engineering University of Sheffield

  6. Outline • Project goals • Integration of fault diagnostic tools on the Grid • Engine simulation as a Grid service • Demonstration and application • Security Issues • Conclusions and future work

  7. Project Goals • Integration of modelling, estimation and analysis tools for engine fault diagnostics • Provide a visualisation and decision support environment for engine fault diagnosis and maintenance

  8. Integration of FDI Tools based on SOA • Different Fault Detection and Isolation (FDI) approaches. • Each approach has its own focus; no “silver bullet” • Integration of several FDI tools will provide better decision support for fault diagnosis and condition-based maintenance • The Grid provides the potential HPC power and large data storage capability for implementation of different algorithms • Service-Oriented Architecture (SOA) and the Open Grid Services Architecture (OGSA) for the integration

  9. Engine Simulation as a Grid Service • An Grid service for engine simulation based on the Rolls-Royce engine performance model • Based on the Globus Toolkit 3 (GT3) andthe Open Grid Service Architecture (OGSA) for distributed systems integration • The engine simulation Grid service can be invoked simultaneously in different “Virtual Organisations” for different applications

  10. Features of the Engine Simulation Grid Service • The simulation: • can simulate for different flight operational conditions and requirements, e.g. Idle, Take-off, Climb, Cruise • takes different variables, including Net Thrust, Turbine Temperature, Spool Speed and Fuel Flow, as control input • As Grid services: • GSI enabled secure engine performance simulation via Internet • a bunch of simulation instances generated by the factory service ; different engine simulation can be performed simultaneously • Only lightweight computers or PDAs are needed to perform the engine simulation, while still benefit from high-performance/high-throughput computing power provided by the Grid

  11. Access the Grid Service through Web Browsers • A Web server for accessing the Engine Simulation Grid Service has been developed • Use JSP to invoke the simulation service • Use Web browser to view the engine performance data and the simulation result • Two way SSL authentication via server and client certificates

  12. Engine Simulation for DAME

  13. Applications • A simulation-based fault detection can be performed • Experienced maintenance engineers can use this service to find the problem via on-line simulation • Can be used to confirm the fault assumption • Can be invoked by different fault diagnostic algorithms Residual generation: Simulator-based approach

  14. Security Issues • The secure sensitive engine model and user data need to be protected! • Challenges: • Eavesdropping • Tampering • Impersonation • Current solutions: • Symmetric-Key encryption • Public-Key encryption • Digital Signatures using PKI • Certificate-Based Authentication • The Engine Simulation Grid Service uses GSI to secure the model and user data • SSL is used to secure the Web and database server

  15. GSI and SSL Implementation • Grid Security Infrastructure(GSI) • the security functionality implemented by Globus Toolkit • Secure Socket Layer(SSL) • a technology for secure connection between Web browsers and servers. • Both use certificates for authentication • SSL uses public key encryption to generate shared secrets; then performs the symmetric encryption • GSI provides the Transport Layer Security and Message Level Security • Transport Layer Security: a grid version of SSL • Message Level Security: based on WS-Security, XML Encryption and XML Signature standards

  16. Conclusions and Future Work • Integration of different fault diagnostic approaches on the Grid • The Engine Simulation Grid Service • The security requirements and current efforts • Potential demonstrations of using the simulation for fault diagnosis will be addressed in the next stage • Further research on the performance-based engine fault diagnosis

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