UM  > 科技學院  > 電腦及資訊科學系
A new framework of simultaneous-fault diagnosis using pairwise probabilistic multi-label classification for time-dependent patterns
Vong C.-M.1; Wong P.-K.2; Ip W.-F.1
2013
Source PublicationIEEE Transactions on Industrial Electronics
ISSN2780046
Volume60Issue:8Pages:3372
Abstract

Simultaneous-fault diagnosis is a common problem in many applications and well-studied for time-independent patterns. However, most practical applications are of the type of time-dependent patterns. In our study of simultaneous-fault diagnosis for time-dependent patterns, two key issues are identified: 1) the features of the multiple single faults are mixed or combined into one pattern which makes accurate diagnosis difficult, 2) the acquisition of a large sample data set of simultaneous faults is costly because of high number of combinations of single faults, resulting in many possible classes of simultaneous-fault training patterns. Under the assumption that the time-frequency features of a simultaneous fault are similar to that of its constituent single faults, these issues can be effectively resolved using our proposed framework combining feature extraction, pairwise probabilistic multi-label classification, and decision threshold optimization. This framework has been applied and verified in automotive engine-ignition system diagnosis based on time-dependent ignition patterns as a test case. Experimental results show that the proposed framework can successfully resolve the issues. © 1982-2012 IEEE.

KeywordAutomotive Applications Fault Diagnosis Feature Extraction Genetic Algorithms (Ga) Ignition Internal Combustion Engines Multiple Signal Classification Principal Component Analysis (Pca) Wavelet Packets
DOI10.1109/TIE.2012.2202358
URLView the original
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS IDWOS:000317864400042
The Source to ArticleScopus
Fulltext Access
Citation statistics
Cited Times [WOS]:34   [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, Fac Sci & Technol, Dept Comp & Informat Sci, Taipa, Macau, Peoples R China
2.Univ Macau, Fac Sci & Technol, Dept Electromech Engn, Taipa, Macau, 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.. A new framework of simultaneous-fault diagnosis using pairwise probabilistic multi-label classification for time-dependent patterns[J]. IEEE Transactions on Industrial Electronics,2013,60(8):3372.
APA Vong C.-M.,Wong P.-K.,&Ip W.-F..(2013).A new framework of simultaneous-fault diagnosis using pairwise probabilistic multi-label classification for time-dependent patterns.IEEE Transactions on Industrial Electronics,60(8),3372.
MLA Vong C.-M.,et al."A new framework of simultaneous-fault diagnosis using pairwise probabilistic multi-label classification for time-dependent patterns".IEEE Transactions on Industrial Electronics 60.8(2013):3372.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Vong C.-M.]'s Articles
[Wong P.-K.]'s Articles
[Ip W.-F.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Vong C.-M.]'s Articles
[Wong P.-K.]'s Articles
[Ip W.-F.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Vong C.-M.]'s Articles
[Wong P.-K.]'s Articles
[Ip W.-F.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.