@inproceedings{4fc073e3642e4b6eb0b5dfe7eb779885,
title = "Analysis of autoregressive coefficients of knock sensor signals for misfire detection in internal combustion engines",
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.",
keywords = "AR modeling, Knock sensor, Misfire detection",
author = "Matthias Rath and Hannes Wegleiter and Georg Brasseur and Riccardo Basso",
year = "2019",
month = may,
day = "1",
doi = "10.1109/I2MTC.2019.8827127",
language = "English",
series = "Conference Record - IEEE Instrumentation and Measurement Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers",
booktitle = "I2MTC 2019 - 2019 IEEE International Instrumentation and Measurement Technology Conference, Proceedings",
address = "United States",
note = "2019 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2019 ; Conference date: 20-05-2019 Through 23-05-2019",
}