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Engine spark ignition diagnosis with wavelet packet transform and case-based reasoning
Vong C.M.; Huang H.; Wong P.K.
2010-08-24
Conference NameThe 2010 IEEE International Conference on Information and Automation
Source Publication2010 IEEE International Conference on Information and Automation, ICIA 2010
Pages565-570
Conference Date20-23 June 2010
Conference PlaceHarbin, China
Abstract

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any fault in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, case-based reasoning (CBR) approach is presented to help solve human diagnosis problem based on the signals captured using a computer-linked automotive scope meter. The advantage of CBR model is that multiple possible diagnoses can be provided to the user, instead of a single most probable diagnosis provided by traditional network-based models such as multi-layer perceptrons (MLP). So, CBR paradigm fits better the requirements of an expert system. CBR is effective but mostly inefficient in time because every instance in a case library must be compared during reasoning. To overcome this inefficiency, case base maintenance (CBM) technique is employed. Considering the ignition patterns captured by scope meter are very similar. Their difference can only be compared with extracted important signal features. Hence, wavelet packet transform (WPT) was proposed for feature extraction. ©2010 IEEE.

KeywordCase Base Maintenance Case Based Reasoning Engine Spark Ignition Signal Analysis Wavelet Packet Transform
DOI10.1109/ICINFA.2010.5512400
URLView the original
Language英语
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Vong C.M.,Huang H.,Wong P.K.. Engine spark ignition diagnosis with wavelet packet transform and case-based reasoning[C],2010:565-570.
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