Change search
ReferencesLink to record
Permanent link

Direct link
Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
2011 (English)Licentiate thesis, monograph (Other academic)
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.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2011. , 169 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1490
Keyword [en]
Automated planning, diagnosis, automotive industry, troubleshooting, Bayesian networks
National Category
Computer Science
URN: urn:nbn:se:liu:diva-67522Local ID: LiU–Tek–Lic–2011:29ISBN: 978-91-7393-151-9 (print)OAI: diva2:411037
2011-06-09, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Available from: 2011-05-10 Created: 2011-04-15 Last updated: 2013-08-29Bibliographically approved

Open Access in DiVA

Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis(1117 kB)1983 downloads
File information
File name FULLTEXT01.pdfFile size 1117 kBChecksum SHA-512
Type fulltextMimetype application/pdf
cover(41 kB)39 downloads
File information
File name COVER01.pdfFile size 41 kBChecksum SHA-512
Type coverMimetype application/pdf

Search in DiVA

By author/editor
Warnquist, Håkan
By organisation
Department of Computer and Information ScienceThe Institute of Technology
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 1983 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 515 hits
ReferencesLink to record
Permanent link

Direct link