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A combined diagnosis system design using model-based and data-driven techniques
Linköping University, Department of Electrical Engineering, Vehicular Systems.
Linköping University, Department of Electrical Engineering, Vehicular Systems.
Linköping University, Department of Electrical Engineering, Vehicular Systems.
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

A hybrid diagnosis system design is proposed that combines model-based and data-driven diagnosis methods for fault isolation. A set of residuals are used to detect if there is a fault in the system and a consistency-based fault isolation algorithm is used to compute all diagnosis candidates that can explain the triggered residuals. To improve fault isolation, diagnosis candidates are ranked by evaluating the residuals using a set of one-class support vector machines trained using data from different faults. The proposed diagnosis system design is evaluated using simulations of a model describing the air-flow in an internal combustion engine.

Place, publisher, year, edition, pages
2016.
Keyword [en]
Fault Isolation, Diagnosis
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-138384OAI: oai:DiVA.org:liu-138384DiVA: diva2:1109436
Conference
Conference on Control and Fault-Tolerant Systems (SysTol’16)
Available from: 2017-06-14 Created: 2017-06-14 Last updated: 2017-06-14

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
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Output format
  • html
  • text
  • asciidoc
  • rtf