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A discernibility matrix primitive based rule extraction method for wear pattern recognition of diesel engine from incomplete data

  • Wentao Huang*
  • , Weijie Wang
  • , Qingxin Meng
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to extract simple and certain diagnostic rules for wear pattern recognition of diesel engine from incomplete data, a method is proposed to directly extract decision rules for fault diagnosis. After defining the discernibility matrix primitive, the definition of object-oriented discernibility matrix in incomplete decision table for fault diagnosis is also proposed. Using these concepts, the object-oriented discernibility function is constructed. With the basic equivalent forms in proposition logic such as distribution laws, absorption laws, a method is proposed to compute the minimal object-oriented reductions. With the method, the diagnostic decision rules are successfully extracted for engine wear pattern from incomplete data so that the simple and certain rule set is obtained.

Original languageEnglish
Title of host publicationProceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08
Pages1956-1960
Number of pages5
DOIs
StatePublished - 2008
Event7th World Congress on Intelligent Control and Automation, WCICA'08 - Chongqing, China
Duration: 25 Jun 200827 Jun 2008

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference7th World Congress on Intelligent Control and Automation, WCICA'08
Country/TerritoryChina
CityChongqing
Period25/06/0827/06/08

Keywords

  • Diesel engine
  • Discernibility matrix primitive
  • Incomplete data
  • Pattern recognition
  • Rule extraction
  • Wear

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