Statistical pattern recognition for TWC diagnosis

Ted Kostek, Matthew Franchek

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ideas from statistical pattern recognition are applied to the problem of diagnosing degraded automotive three-way catalysts using oxygen sensors. A brief overview of statistical pattern recognition is given. A novel method of processing the oxygen sensor signals converts the time signals into ensembles of vectors. Using the tools of pattern recognition, the ensembles are described statistically, and classifiers are derived from the statistical descriptions. The resulting classifiers are tested against four different aging categories, and the performance is quantified via the operating characteristic. Techniques to achieve arbitrary levels of performance are discussed.

Original languageEnglish
Title of host publicationSAE Technical Papers
DOIs
StatePublished - Dec 1 2005
Event2005 SAE World Congress - Detroit, MI, United States
Duration: Apr 11 2005Apr 14 2005

Other

Other2005 SAE World Congress
CountryUnited States
CityDetroit, MI
Period4/11/054/14/05

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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