《机电工程》杂志社科技期刊核心期刊论文投稿机电一体化机械、仪表电工自动化、计算机浙江大学主办

Introduction

International Standard Serial Number:

ISSN 1001-4551

Sponsor:

Zhejiang University;

Zhejiang Machinery and Electrical Group

Edited by:

Editorial of Journal of Mechanical & Electrical Engineering

Chief Editor:

ZHAO Qun

Vice Chief Editor:

TANG ren-zhong,

LUO Xiang-yang

Tel:

86-571-87041360,87239525

Fax:

86-571-87239571

Add:

No.9 Gaoguannong,Daxue Road,Hangzhou,China

P.C:

310009

E-mail:

meem_contribute@163.com

Bearing incipient fault diagnosis based on VMD and enhanced envelope spectrum

Published:2022-09-22 author:HAN Peng-peng, HE Chang-bo, LU Si-liang. Browse: 556 Check PDF documents

Bearing incipient fault diagnosis based on VMD and

enhanced envelope spectrum

HAN Peng-peng, HE Chang-bo, LU Si-liang

(National Engineering Laboratory of Energy-Saving Motor and

Control Technology, Anhui University, Hefei 230601, China)

Abstract: Aiming at the problem that the early fault signal of rolling bearing was easily interfered by noise, resulting in low signal-to-noise ratio of the signal, combining the advantages of VMD and enhanced envelope spectrum algorithms, a bearing fault diagnosis method based on the combination of genetic algorithm optimization VMD and enhanced envelope spectrum was proposed. First, the envelope entropy and square envelope spectral kurtosis were used as the fitness function of the genetic algorithm to obtain the optimal parameters of the VMD algorithm. The optimal number of the decomposed components and penalty factor were obtained. Subsequently, the bearing fault signal was decomposed using the VMD with the obtained optimal parameters. The component with the minimum fitness value was selected. Finally, in order to verify the effectiveness of this method, the bearing fault types were identified by two measured signals of Brushless DC motor bearing and life-cycle accelerated degradation bearing. The research results indicate that compared with the traditional method, the output signal-to-noise ratio of the method based on VMD and enhanced envelope spectrum is increased by 5.94 dB on average, and the early bearing failures can be identified up to 600 min in advance for full-life bearing degradation data. The proposed method has advantages including high output SNR and good flexibility, and hence shows great potential applications in bearing weak signal detection and incipient fault diagnosis.

Key words: bearing fault diagnosis; incipient fault;variational mode decomposition (VMD); genetic algorithm(GA); cyclostationary analysis; enhanced envelope spectrum

Advanced Search

Online Office System

Chinese Core Periodicals
Chinese Sci-tech Core Periodicals
SA, INSPEC Indexed
CSA: T Indexed
UPD:Indexed