Research on Gasoline Engines Health Monitoring and Fault Diagnosis based on Vibration Signal Analysis

Qiuqin Yue, Jielin Zhou

2018

Abstract

Aiming at research on engine health monitoring and fault diagnosis based on the characteristics of the surface vibration signals measured from the engine, a measured method by using wireless acceleration sensor is proposed in this paper. The basic characteristics of engine vibration signal taking the Chevrolet Epica 2HO automotive engine as an example was measured in this paper. The original measured data was pre-processed using the Fast Fourier Transform (FFT) to suppress abnormal interference of noise, and avoid the pseudo mode functions. Finally, the vibration signals of automotive engine are analyzed and the results show that the method is feasible and effective in feature extraction and condition evaluation of engine health monitoring and fault diagnosis.

Paper Citation

in Harvard Style

Yue Q. and Zhou J. (2018). Research on Gasoline Engines Health Monitoring and Fault Diagnosis based on Vibration Signal Analysis.In 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT, ISBN 978-989-758-312-4, pages 440-443. DOI: 10.5220/0006972304400443

in Bibtex Style

@conference{icectt18,
author={Qiuqin Yue and Jielin Zhou},
title={Research on Gasoline Engines Health Monitoring and Fault Diagnosis based on Vibration Signal Analysis},
booktitle={3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,},
year={2018},
pages={440-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006972304400443},
isbn={978-989-758-312-4},
}

in EndNote Style

TY - CONF

JO - 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,
TI - Research on Gasoline Engines Health Monitoring and Fault Diagnosis based on Vibration Signal Analysis
SN - 978-989-758-312-4
AU - Yue Q.
AU - Zhou J.
PY - 2018
SP - 440
EP - 443
DO - 10.5220/0006972304400443