基于变分模态分解改进方法的滚动轴承故障特征提取.pdf

2016 年 12 月 图 学 学 报 December 2016 第 37 卷 第6 期 JOURNAL OF GRAPHICS Vol.37 No.6 基于变分模态分解改进方法的滚动轴承 故障特征提取 1 2 1 高红玮 ， 张丽荣 ， 侯少杰 (1. 河北经贸大学计算机中心，河北 石家庄 050061 ；2. 河北经贸大学旅游学院，河北 石家庄 050061) 摘 要：针对滚动轴承早期故障振动信号信噪比低、故障特征提取困难的问题，提出了基 于多相关-变分模态分解(MC-VMD)的滚动轴承故障诊断方法。首先对多加速度传感器采集到的 信号进行多相关处理以突出故障信号特征；然后通过 VMD 自适应地将信号分解成多个本征模 态分量(IMFs) ，运用谱峭度法和包络解调对相关峭度较大的分量进行分析；最后通过包络谱识 别出滚动轴承的工作状态和故障类型。将该方法应用到滚动轴承故障实例数据中，实验结果表 明，该方法可有效提取滚动轴承故障特征频率信息。 关 键 词：多相关；变分模态分解；滚动轴承；谱峭度 中图分类号：TP 206.3 TH 133.33 DOI ：10.11996/JG.j.2095-302X.2016060862 文献标识码：A 文 章 编 号：2095-302X(2016)06-0862-06 Rolling Bearing Fault Feature Extraction Based on Improved Variational Mode Decomposition 1 2 1 Gao Hongwei , Zhang Lirong , Hou Shaojie (1. Economics and Business Computer Center, Hebei University, Shijiazhuang Hebei 050061, China; 2. Economics and Business Institute for Tourism Studies, Hebei University, Shijiazhuang Hebei 050061, China) Abstract: In order to solve the problems that the fault feature of rolling bearing in early failure period is difficult to extract, a method for fault diagnosis of rolling bearings based on multi-correlation variational mode decomposition (MC-VMD) was presented. First, vibration signal is jointly acquired through multiple acceleration sensors and the multi-correlation process is made for the signal in order to prominent fault signal cha