Residual generation and statistical pattern recognition for engine misfire diagnostics

Andrew W. Osburn, Theodore M. Kostek, Matthew A. Franchek

Research output: Contribution to journalArticle

31 Scopus citations

Abstract

Methods for diagnosing misfire in internal combustion engines are presented in this paper. Crank-angle domain digital filters are used to extract features from the measured engine speed signal that are characteristic of misfire. Features for intermittent and continuous misfires are developed separately, since the engine speed responses for intermittent and continuous misfires are distinctly different. Also, the influence of crankshaft torsional vibration and repeatable measurement errors must be addressed differently in each case. The outputs from the digital filters serve as inputs to a pattern recognition network based on linear parametric classifiers. Experimental results from implementation on a Ford 4.6L V-8 engine are provided.

Original languageEnglish (US)
Pages (from-to)2232-2258
Number of pages27
JournalMechanical Systems and Signal Processing
Volume20
Issue number8
DOIs
StatePublished - Nov 2006

Keywords

  • Internal combustion engines
  • Misfire diagnostics
  • Statistical pattern recognition

ASJC Scopus subject areas

  • Signal Processing
  • Mechanical Engineering

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