Analysis of autoregressive coefficients of knock sensor signals for misfire detection in internal combustion engines

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Abstract

Current emission laws require a misfire detection rate of 100% which can only be robustly achieved by the combination of different detection strategies. State of the art detection is done by analyzing the engine speed drops. In order to maximize the detection rate, vibration signals acquired by a broadband knock sensor are investigated for their suitability for misfire detection. In this work the vibration signal is modeled as an autoregressive process described by polynomial filter coefficients. The influences of misfire events on those filter coefficients are analyzed. As a second method, the power of the vibration signal is analyzed. Cross-influences on the autoregressive coefficients from the engine speed are analyzed. Those influences have to be considered when designing an adaptive threshold-based method for misfire detection based on the presented methods.

Originalspracheenglisch
TitelI2MTC 2019 - 2019 IEEE International Instrumentation and Measurement Technology Conference, Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers
ISBN (elektronisch)9781538634608
DOIs
PublikationsstatusVeröffentlicht - 1 Mai 2019
Veranstaltung2019 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2019 - Auckland, Neuseeland
Dauer: 20 Mai 201923 Mai 2019

Publikationsreihe

NameConference Record - IEEE Instrumentation and Measurement Technology Conference
Band2019-May
ISSN (Print)1091-5281

Konferenz

Konferenz2019 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2019
LandNeuseeland
OrtAuckland
Zeitraum20/05/1923/05/19

ASJC Scopus subject areas

  • !!Electrical and Electronic Engineering

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