Fault Feature Extraction of Diesel Engine Based on Second Generation Wavelet and HHT

DOI

10.2991/icmcm-16.2016.122How to use a DOI?

Keywords

Second generation wavelet; EMD; Hilbert transform; Feature extraction; Diesel engine

Abstract

Aiming at difficulty of weak characteristics of the nonlinear and low signal-to-noise ratio signals measured from diesel engine, a novel method combining second generation wavelet denoising and Hilbert Huang Transform(HHT) is proposed, and is used for feature extraction and condition evaluation of vibration signals measured from diesel engine. Firstly, the original data is pre-processed using second generation wavelet to suppress abnormal interference of noise and obtain intrinsic mode functions(IMFs) by using EMD. Then the instantaneous frequency and amplitude are computed by Hilbert transform and Hilbert marginal spectrum is obtained, which can exactly provide the energy distribution of the signal with the change of instantaneous frequency. The vibration signals of diesel engine piston-liner wear are analyzed and the results show that the proposed method is feasible and effective in feature extraction and condition evaluation of diesel engine faults.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fengli Wang
AU  - Yannian Cai
AU  - Sihong Li
AU  - Hui Xing
PY  - 2016/12
DA  - 2016/12
TI  - Fault Feature Extraction of Diesel Engine Based on Second Generation Wavelet and HHT
BT  - Proceedings of the 2016 7th International Conference on Mechatronics, Control and Materials (ICMCM 2016)
PB  - Atlantis Press
SP  - 653
EP  - 656
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmcm-16.2016.122
DO  - 10.2991/icmcm-16.2016.122
ID  - Wang2016/12
ER  -