Gear Fault Diagnosis Based on Support Vetor Machine

Xingyan Yao, Chuanwen Liu, Xiping He

2018

Abstract

Vibration signals analysis are commonly used in mechanical fault diagnosis, especially in vehicles. The vibration signal contains the information of fault in the gear failure, but this information does not directly characterize all kinds of faults. The feature of fault types of the acceleration signal in time-frequency domain was firstly obtained in the time domain and frequency domain analysis. And wavelet packet decomposition analysis is adopted in time-frequency domain analysis. The support vector machine classification was employed to get the fault characteristic. The results show that, the energy spectrum feature of time-frequency based on wavelet decomposition is the best choices for the fault identification of gear.

Paper Citation

in Harvard Style

Yao X., Liu C. and He X. (2018). Gear Fault Diagnosis Based on Support Vetor Machine.In 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT, ISBN 978-989-758-312-4, pages 146-149. DOI: 10.5220/0006966601460149

in Bibtex Style

@conference{icectt18,
author={Xingyan Yao and Chuanwen Liu and Xiping He},
title={Gear Fault Diagnosis Based on Support Vetor Machine},
booktitle={3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,},
year={2018},
pages={146-149},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006966601460149},
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 - Gear Fault Diagnosis Based on Support Vetor Machine
SN - 978-989-758-312-4
AU - Yao X.
AU - Liu C.
AU - He X.
PY - 2018
SP - 146
EP - 149
DO - 10.5220/0006966601460149