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Simultaneous-fault diagnosis of automotive engine ignition systems using prior domain knowledge and relevance vector machine
Vong C.-M.1; Wong P.-K.2; Ip W.-F.3; Chiu C.-C.1
2013
Source PublicationMathematical Problems in Engineering
ISSN1024123X
Volume2013
Abstract

Engine ignition patterns can be analyzed to identify the engine fault according to both the specific prior domain knowledge and the shape features of the patterns. One of the challenges in ignition system diagnosis is that more than one fault may appear at a time. This kind of problem refers to simultaneous-fault diagnosis. Another challenge is the acquisition of a large amount of costly simultaneous-fault ignition patterns for constructing the diagnostic system because the number of the training patterns depends on the combination of different single faults. The above problems could be resolved by the proposed framework combining feature extraction, probabilistic classification, and decision threshold optimization. With the proposed framework, the features of the single faults in a simultaneous-fault pattern are extracted and then detected using a new probabilistic classifier, namely, pairwise coupling relevance vector machine, which is trained with single-fault patterns only. Therefore, the training dataset of simultaneous-fault patterns is not necessary. Experimental results show that the proposed framework performs well for both single-fault and simultaneous-fault diagnoses and is superior to the existing approach. © 2013 Chi-Man Vong et al.

DOI10.1155/2013/974862
URLView the original
Indexed BySCI
Language英语
WOS Research AreaEngineering ; Mathematics
WOS SubjectEngineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000316496400001
The Source to ArticleScopus
Fulltext Access
Citation statistics
Cited Times [WOS]:8   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Corresponding AuthorVong C.-M.
Affiliation1.Univ Macau, Dept Comp & Informat Sci, Taipa, Peoples R China
2.Univ Macau, Dept Electromech Engn, Taipa, Peoples R China
3.Univ Macau, Fac Sci & Technol, Taipa, Peoples R China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Vong C.-M.,Wong P.-K.,Ip W.-F.,et al. Simultaneous-fault diagnosis of automotive engine ignition systems using prior domain knowledge and relevance vector machine[J]. Mathematical Problems in Engineering,2013,2013.
APA Vong C.-M.,Wong P.-K.,Ip W.-F.,&Chiu C.-C..(2013).Simultaneous-fault diagnosis of automotive engine ignition systems using prior domain knowledge and relevance vector machine.Mathematical Problems in Engineering,2013.
MLA Vong C.-M.,et al."Simultaneous-fault diagnosis of automotive engine ignition systems using prior domain knowledge and relevance vector machine".Mathematical Problems in Engineering 2013(2013).
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