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A Bayesian Approach to Fault Isolation with Application to Diesel Engine Diagnosis
Scania CV AB.
Scania CV AB.
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-1927-1690
2006 (English)In: DX’06, 17th International Workshop on Principles of Diagnosis, Peñaranda de Duero, Burgos, Spain, June 26-28, 2006 / [ed] Carlos Alonso González, Teresa Escobet, and Belarmino Pulido, 2006, 211-218 p.Conference paper (Refereed)
Abstract [en]

This paper considers a Bayesian approach to fault isolation. Given a set of measurements from the system, and a set of possible faults, the task is to calculate the probability that the faults are present. This probability can then be used to rank the faults, or for decisions on fault sccomodation. The method requires the conditional probability distribution desccribing how the measurements react to the faults. In particular, the structure of dependencies between the tests is important. Knowing the structure facilitates efficient computation methods and makes it possible to reduce the memory capacity needed. In this paper, the structure is estimated from training data using Bayesian methods. The method is applied to diagnosis of the gas flow in a diesel engine.

Place, publisher, year, edition, pages
2006. 211-218 p.
Keyword [en]
fault isolation, fault location, diagnosis, inference, probability, Bayeisan probability
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-57724OAI: diva2:472538
17th Workshop on Principles for Diagnosis, Peñaranda de Duero, Burgos, Spain, June 26-28, 2006
QC 20120104Available from: 2012-01-18 Created: 2012-01-04 Last updated: 2013-09-05Bibliographically approved

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