LiU Electronic Press
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Author:
Warnquist, Håkan (Linköping University, Department of Computer and Information Science) (Linköping University, The Institute of Technology)
Title:
Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis
Department:
Linköping University, Department of Computer and Information Science
Linköping University, The Institute of Technology
Publication type:
Licentiate thesis, monograph (Other academic)
Language:
English
Place of publ.: Linköping Publisher: Linköping University Electronic Press
Pages:
169
Series:
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971; 1490
Year of publ.:
2011
URI:
urn:nbn:se:liu:diva-67522
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-67522
ISBN:
978-91-7393-151-9
Local ID:
LiU–Tek–Lic–2011:29
Subject category:
Computer Science
SVEP category:
Computer science
Keywords(en) :
Automated planning, diagnosis, automotive industry, troubleshooting, Bayesian networks
Abstract(en) :

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.

Presentation:
2011-06-09, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Degree:
Licentiate of Engineering
Supervisor:
Doherty, Patrick, Professor (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Kvarnström, Jonas, Dr (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Nyberg, Mattias, Dr (Linköping University, Department of Electrical Engineering) (Linköping University, The Institute of Technology)
Opponent:
Frisk, Erik, Dr (Linköping University, Department of Electrical Engineering) (Linköping University, The Institute of Technology)
Available from:
2011-05-10
Created:
2011-04-15
Last updated:
2013-08-29
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