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Bayesian belief networks for guidedremote diagnostics and troubleshootingof heavy vehicles
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Bayesianska nätverk för guidadfjärrdiagnostik och åtgärdsplanering avtunga fordon (Swedish)
Abstract [sv]

Kostnadreducering och eektivisering av reparationer (t.ex i bilindustrin) har varit malet for forskningen kring guidad diagnostik i snart tvadecennier [ 1], med en onskan till intuitiv felsokning och reparation utan tidigare expert kunskaper. Detta betyder att automation vid diagnostik har blivit en nodvandighet dar det ar mojligt att forstakomplexa system samtidigt som operatoren ges tillrackligt med stod och expertkunskaper fr att kunna tillfora kompetent assistans. Detta examensarbete som utfordes paScania CV AB undersoker hur ett sadant system skulle utformas och prestera samtidigt som arbetet ligger till grund for vidare utveckling av guidad fjarrdiagnostik hos Scania.

Resultatet kommer att behandla tre analysomraden. Ett, dem observationer fran fordonet som ar indikationer om ett felaktigt system. Tva, anvandning av ett Basianskt natverk for att gora en diagnos pasystemet samt undersoka hurvida tillvagagangasattet ar eektivt eller inte for den intiutiva kanslan. Tre, en studie och implementation av en eektiv felsokningsalgoritm som minimerar reparationskostnaden baserad paden givna diagnosen, kostnad for reparationav komponenter samt reparationstiden. Examensarbetet kommer forst att presenteras med en djupgaende teoridel och foljs av implementation av teorin till en funktionell prototyp.

Abstract [en]

Intuitive troubleshooting and fault repair without the need of prior expert knowledge of automobiles has become essential in an aim for cost-minimization and eectiveness of repairs, it has been a focus in troubleshooting research for the past decade or two[  1]. This calls for an automated diagnosis system that is simple to understand and operate whilst at the same time provides the operator with the expert knowledge required for competent assistance. Thismaster thesis conducted at Scania CV AB will investigate how such a system would function and perform, providing a ground work for further development.

The result will incorporate three aspects of analysis. First, the observations from the vehicle indicating that something is wrong or faulty. Second, the use of a Bayesian network, a model structure that describes probabilistic relationships and dependencies among system variables, for diagnostic purposes and to examine its haul on intuitive understanding of the system faults. Third, an implementation and study of a troubleshooting algorithm that will minimize the cost of repair based on an easy calculated metric that takes into consideration the probability of fault, cost of observation and the cost of repair (and indirectly also the mean repair time). Given a particular diagnosis, an optimized action plan and repair sequence is given. A thorough review of the underlying theory will be provided for the reader in the rst part of the report, where a slight deviation will be made to further investigate the use of  Bayesian lters and its eect on the  a priori probabilities used in the Bayesian model. In the nal part the reader will be guided through the implementation of the given theory and emersion of a working prototype.

Place, publisher, year, edition, pages
2017. , p. 98
Series
MMK 2013:58 MDA 45
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-209906OAI: oai:DiVA.org:kth-209906DiVA, id: diva2:1115022
Supervisors
Examiners
Available from: 2017-06-26 Created: 2017-06-26 Last updated: 2017-06-26Bibliographically approved

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