UM  > 科技學院
Support Vector Classification using Domain Knowledge and Extracted Pattern Features for Engine Ignition System Diagnosis
Chi-man Vong1; Pak-kin Wong2; Weng-fai Ip3
2010-10-01
Source PublicationJournal of the Chinese Society of Mechanical Engineers
ISSN0257-9731
Volume31Issue:5Pages:363-373
Abstract

In traditional way, whenever there is any fault in an automotive engine ignition system and change of engine conditions, an automotive mechanic can perform an analysis on the ignition pattern of the engine to check any exceptional symptoms, based on specific domain knowledge (domain features of an ignition pattern). In this paper, support vector machine (SVM) is presented to help solve manual diagnosis problem based on not only the domain features, but also the shape features of patterns captured by using a computer-linked automotive scope meter. Since raw ignition patterns captured by the scope meter are very similar, wavelet packet transform (WPT) is proposed for feature extraction so that the ignition patterns can be comparable under the extracted shape features. However, there exist many redundant points in the extracted features which will degrade the diagnosis performance and speed. Therefore, kernel principal components analysis (KPCA) is employed for dimension reduction. Three different SVMs were constructed for diagnosis and comparison. They were built by (i) using raw captured ignition patterns, (ii) purely extracted pattern features, and (iii) domain features along with extracted pattern features. Experimental results show that linear kernel SVM using domain features and extracted pattern features generates the highest accuracy.

KeywordSupport Vector Machine Engine Ignition Pattern Analysis Wavelet Packet Transform Kernel Principal Component Analysis
Indexed BySCI
Language英语
WOS Research AreaEngineering
WOS SubjectEngineering, Mechanical
WOS IDWOS:000283763200001
Fulltext Access
Citation statistics
Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computers and Information Science, Faculty of Science and Technology, University of Macau, Macau
2.Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macau
3.Faculty of Science and Technology, University of Macau, Macau
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Chi-man Vong,Pak-kin Wong,Weng-fai Ip. Support Vector Classification using Domain Knowledge and Extracted Pattern Features for Engine Ignition System Diagnosis[J]. Journal of the Chinese Society of Mechanical Engineers,2010,31(5):363-373.
APA Chi-man Vong,Pak-kin Wong,&Weng-fai Ip.(2010).Support Vector Classification using Domain Knowledge and Extracted Pattern Features for Engine Ignition System Diagnosis.Journal of the Chinese Society of Mechanical Engineers,31(5),363-373.
MLA Chi-man Vong,et al."Support Vector Classification using Domain Knowledge and Extracted Pattern Features for Engine Ignition System Diagnosis".Journal of the Chinese Society of Mechanical Engineers 31.5(2010):363-373.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chi-man Vong]'s Articles
[Pak-kin Wong]'s Articles
[Weng-fai Ip]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chi-man Vong]'s Articles
[Pak-kin Wong]'s Articles
[Weng-fai Ip]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chi-man Vong]'s Articles
[Pak-kin Wong]'s Articles
[Weng-fai Ip]'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.