基于改进变分模态提取的轴承早期故障诊断
Early Fault Diagnosis of Bearings Based on Improved Variational Mode Extraction
张家军 1马萍 1彭炫 2张宏立1
作者信息
- 1. 新疆大学 电气工程学院,乌鲁木齐 830017
- 2. 新疆大学 工程训练中心,乌鲁木齐 830017
- 折叠
摘要
针对变分模态提取(variational mode extraction,VME)在强背景噪音下初始中心频率难以确定的问题,提出了基于谱相干引导变分模态提取(SC-VME)的滚动轴承故障诊断方法.首先,引入谱相干(spectral coherence,SC)算法对信号进行处理,得到由循环频率和频谱频率构成的双频域,并结合1/3-二叉树滤波器组得到改进包络谱(improved envelope spectrum,IES);然后,以轴承故障特征频率识别的局部特征能量与频带中的IES能量占比为诊断指标,构建诊断性指示图,据此确定VME期望模态的初始中心频率;最后,通过对提取的期望模态进行包络谱分析,实现滚动轴承早期故障诊断.通过仿真和试验信号分析,结果表明所提SC-VME方法准确性更高、用时更短、效果更优.
Abstract
To overcome the difficulty in determining the initial center frequency of variational mode extrac-tion(VME)under strong background noise,a rolling bearing fault diagnosis method based on spectral co-herence-guided variational mode extraction(SC-VME)was proposed.First,a spectral coherence(SC)al-gorithm was introduced to process the signal to obtain the dual frequency domain consisting of cyclic fre-quency and spectrum frequency,and an improved envelope spectrum(IES)was obtained by combining 1/3-binary tree filter banks.Then,taking the proportion of local characteristic energy of bearing fault char-acteristic frequency recognition and IES energy in frequency band as diagnostic indexes,a diagnostic indica-tor diagram was constructed to determine the initial center frequency of VME expected mode.Finally,early fault diagnosis of rolling bearing is realized by envelope spectrum analysis of extracted expected mode.The results of simulation and experimental signal analysis show that the proposed SC-VME method has higher accuracy,shorter time and better effect.
关键词
滚动轴承/谱相干/变分模态提取/早期故障诊断Key words
rolling bearings/spectral coherence/variational mode extraction/early fault diagnosis引用本文复制引用
基金项目
国家自然科学基金资助项目(52065064)
国家自然科学基金资助项目(52267010)
新疆维吾尔自治区自然科学基金资助项目(2022D01E33)
新疆维吾尔自治区自然科学基金资助项目(2022D01C367)
出版年
2024
NETL
NSTL
维普
万方数据