CBR for Fault Analysis in DAME

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CBR for Fault Analysisin DAME

• Max Ong
• University of Sheffield

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Overview

• Overview of presentation
• Introduction to Case-Based Reasoning (CBR)
  technology
• CBR for Fault Analysis
• Maintenance Advisor
• Grid Service Implementation
• User interface to the Grid Service
• Related Work
• MEAROS
• CBR Workflow Advisor

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Case-Based Reasoning

• CBR is a mature, low-risk subfield of A.I.
• Primary knowledge source
• a memory of stored cases recording specific prior
  episodes
• not generalised rules
• New solutions generated by adapting relevant
  cases from memory to suit new situations

Retrieve
Propose Solution
Adapt
Justify
Criticize
Evaluate
Reasoning by remembering, reasoning is
remembered.
Store
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Case-Based Reasoning

• What is a case?
• A case is a contextualised piece of knowledge
  representing an experience that teaches a lesson
  fundamental to achieving the goals of the
  reasoner. (Kolodner, 1993)
• Cases link together knowledge that belongs
  together
• Information concerning the fault
• Response to the fault
• Effects of those responses

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CBR Knowledge

• Casebase
• Repository of fault cases
• Cases represent individual engine fault events
  and maintenance actions
• Knowledge Model
• Contains general knowledge about a specific field
  of application
• Comprises the data structure (data model), the
  relationship between values within the data
  (valuation models) and information for defining
  application-specific vocabulary in the data
• Valuation Model
• Defines the similarities and evaluations of
  individual pieces of data in relation to each
  other
• Facilitates knowledge-based, intelligent searches
  (directed search)

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CBR Search

• CBR Tool Implements
• Nearest Neighbour (k-NN) algorithm

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CBR Induction

• Inductive Retrieval
• Induction - ID3 Algorithm
• Knowledge-Guided Induction
• Example

1. Discriminate by EPR
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CBR Maintenance Advisor

• CBR Maintenance Advisor
• Emulates the diagnostic skill of an experienced
  maintenance engineer
• Provides the user with best practice advice
  when confronted with a set of fault symptoms
• Provides a confidence measure for each suggested
  solution
• Facilitates the processing of logistic data,
  current and historical fault data to
  intelligently isolate an engine problem
• Some common misconceptions
• CBR is a relational database of engine faults
• CBR is only a search engine

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CBR Maintenance Advisor

• Why the Grid?
• Collaborative working environment (virtual
  organisation)
• Distributed data
• Interaction with other services
• High performance computing (large casebase
  computation)
• Scalability
• Delivery via Grid Services with security

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CBR Maintenance Advisor Implementation
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CBR Maintenance Advisor Implementation
CBR Maintenance Advisor - Grid Service

• Deployed as a service on the Grid with Globus 3
  Toolkit
• Accessible by user via a web browser across the
  Internet
• Secure access with user and host authentication,
  SSL encryption.
• Access to fault information and knowledge gained
  from fault diagnosis processes
• Obtain maintenance advice in form of appropriate
  maintenance action

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CBR Maintenance Advisor Implementation

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CBR Maintenance Advisor Implementation
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CBR Maintenance Advisor Implementation
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• Quick summary
• Case-Based Reasoning (CBR) technology
• CBR for Fault Analysis
• Maintenance Advisor Service in DAME
• Globus 3 Grid Service Implementation
• Related work
• MEAROS
• CBR Workflow Advisor

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MEAROS Modular Engine Arisings Overhaul
Simulation

• Removal of aircraft engines is expensive,
  significant fraction of operating costs
• MEAROS enables optimal preventative
  maintenance strategies to be determined
• MEAROS within virtual maintenance environment
  can enhance fleet management of aircraft and
  engines
• MEAROS simulation is a very compute-intensive
  process
• The Grid offers high-performance computing
  resources, enabling faster results and quicker
  decisions to facilitate maintenance planning