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A Toolbox for Analysis and Design of Model Based Diagnosis Systems for Large Scale Models
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-0808-052X
2017 (English)In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2017, Vol. 50, no 1, p. 3287-3293Conference paper, Published paper (Refereed)
Abstract [en]

To facilitate the use of advanced fault diagnosis analysis and design techniques to industrial sized systems, there is a need for computer support. This paper describes a Matlab toolbox and evaluates the software on a challenging industrial problem, air-path diagnosis in an automotive engine. The toolbox includes tools for analysis and design of model based diagnosis systems for large-scale differential algebraic models. The software package supports a complete tool-chain from modeling a system to generating C-code for residual generators. Major design steps supported by the tool are modeling, fault diagnosability analysis, sensor selection, residual generator analysis, test selection, and code generation. Structural methods based on efficient graph theoretical algorithms are used in several steps. In the automotive diagnosis example, a diagnosis system is generated and evaluated using measurement data, both in fault-free operation and with faults injected in the control-loop. The results clearly show the benefit of the toolbox in a model-based design of a diagnosis system. Latest version of the toolbox can be downloaded at faultdiagnosistoolbox.github.io. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2017. Vol. 50, no 1, p. 3287-3293
Series
IFAC Papers Online, ISSN 2405-8963
Keywords [en]
Fault diagnosis; software tool; toolbox; Matlab; automotive engine
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:liu:diva-147467DOI: 10.1016/j.ifacol.2017.08.504ISI: 000423964800047OAI: oai:DiVA.org:liu-147467DiVA, id: diva2:1205862
Conference
20th World Congress of the International-Federation-of-Automatic-Control (IFAC)
Available from: 2018-05-15 Created: 2018-05-15 Last updated: 2018-05-15

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Frisk, ErikKrysander, MattiasJung, Daniel
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CiteExportLink to record
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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
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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