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Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis

Warnquist, Håkan, 1982- (författare)
Linköpings universitet,Institutionen för datavetenskap,Tekniska högskolan
Doherty, Patrick, Professor (preses)
Linköpings universitet,KPLAB - Laboratoriet för kunskapsbearbetning,Tekniska högskolan
Kvarnström, Jonas, Dr (preses)
Linköpings universitet,KPLAB - Laboratoriet för kunskapsbearbetning,Tekniska högskolan
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Nyberg, Mattias, Dr (preses)
Linköpings universitet,Institutionen för systemteknik,Tekniska högskolan
Frisk, Erik, Dr (opponent)
Linköpings universitet,Institutionen för systemteknik,Tekniska högskolan
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 (creator_code:org_t)
ISBN 9789173931519
Linköping : Linköping University Electronic Press, 2011
Engelska 169 s.
Serie: Linköping Studies in Science and Technology. Thesis, 0280-7971 ; 1490
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)
Abstract Ämnesord
Stäng  
  • This licentiate thesis considers computer-assisted troubleshooting of complex products such as heavy trucks. The troubleshooting task is to find and repair all faulty components in a malfunctioning system. This is done by performing actions to gather more information regarding which faults there can be or to repair components that are suspected to be faulty. The expected cost of the performed actions should be as low as possible.The work described in this thesis contributes to solving the troubleshooting task in such a way that a good trade-off between computation time and solution quality can be made. A framework for troubleshooting is developed where the system is diagnosed using non-stationary dynamic Bayesian networks and the decisions of which actions to perform are made using a new planning algorithm for Stochastic Shortest Path Problems called Iterative Bounding LAO*.It is shown how the troubleshooting problem can be converted into a Stochastic Shortest Path problem so that it can be efficiently solved using general algorithms such as Iterative Bounding LAO*.  New and improved search heuristics for solving the troubleshooting problem by searching are also presented in this thesis.The methods presented in this thesis are evaluated in a case study of an auxiliary hydraulic braking system of a modern truck. The evaluation shows that the new algorithm Iterative Bounding LAO* creates troubleshooting plans with a lower expected cost faster than existing state-of-the-art algorithms in the literature. The case study shows that the troubleshooting framework can be applied to systems from the heavy vehicles domain.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

Automated planning
diagnosis
automotive industry
troubleshooting
Bayesian networks
Computer science
Datavetenskap

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