[1]邱林江,花小朋,徐 森.基于 CEEMDAN 与自适应阈值降噪的滚动轴承故障诊断[J].机械与电子,2023,41(03):65-70.
　QIU Linjiang,HUA Xiaopeng,XU Sen.Fault Diagnosis of Bearing Based on CEEMDAN and Adaptive Threshold Denoising[J].Machinery & Electronics,2023,41(03):65-70.
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基于 CEEMDAN 与自适应阈值降噪的滚动轴承故障诊断()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
41
期数:
2023年03期
页码:
65-70
栏目:
机电一体化技术
出版日期:
2023-03-31

文章信息/Info

Title:
Fault Diagnosis of Bearing Based on CEEMDAN and Adaptive Threshold Denoising
文章编号:
1001-2257 ( 2023 ) 03-0065-06
作者:
邱林江; 花小朋; 徐 森
盐城工学院信息工程学院,江苏 盐城 224051
Author(s):
QIU Linjiang ;  HUA Xiaopeng ;  XU Sen
( School of Information and Engineering , Yancheng Institute of Technology , Yancheng 224051 , China )
关键词:
故障诊断; 模态分解; 灰色关联分析; 自适应阈值; 降噪
Keywords:
fault diagnosis ;  mode decomposition ;  grey relational analysis ;  adaptive threshold ;  denoising
分类号:
TH133.33
文献标志码:
A
摘要:
针对滚动轴承故障信息受到噪声污染而难以识别的问题,提出一种基于自适应噪声完备集合经验模态分解和自适应阈值降噪( CEEMDAN-ATD )的滚动轴承故障诊断方法。首先对原始振动信号进行 CEEMDAN 分解;其次利用灰色关联分析法( GRA )筛选出噪声主导和信号主导的分量;然后对噪声主导分量分别进行自适应阈值降噪( ATD )处理,并与信号主导分量进行重构;最后通过分析重构信号的 Teager 能量谱实现滚动轴承故障的识别。采用凯斯西储大学轴承数据对所提方法进行验证,并与完全总体经验模态分解 自适应阈值降噪( CEEMD-ATD )和 CEEMDAN 小波阈值降噪( CEEMDAN-WTD ) 2 种方法作比较,结果表明,所提方法表现出较好的自适应性和去噪效果,能够较好地服务于滚动轴承故障诊断。
Abstract:
Aiming at the problem that the fault information of rolling bearing is polluted by noise and difficult to identify , a bearing fault diagnosis method based on adaptive noise complete ensemble empirical mode decomposition and adaptive threshold denoising( CEEMDAN-ATD ) is proposed.First of all , the original vibration signal is decomposed by CEEMDAN.Secondly , the noise-dominant components and signal-dominant components is filtered out by grey relational analysis ( GRA ) .Then , adaptive threshold denoising is performed on the noise dominant components respectively , and reconstruction is performed with the signal dominant components.Finally , the fault identification of rolling bearing is realized by analyzing the Teager energy spectrum of the reconstructed signal.The proposed method is verified by bearing data from Case Western Reserve University.Compared with the two methods of complete global empirical mode decomposition-adaptive threshold denoising( CEEMD-ATD ) and CEEMDAN-wavelet threshold denoising( CEEMDAN-WTD ), the proposed method has good adaptability and denoising effect , and can serve the rolling bearing fault diagnosis well.

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备注/Memo

备注/Memo:
收稿日期: 2022-09-18
基金项目:国家自然科学基金面上项目( 62076215 )
作者简介:邱林江 ( 1998- ),男,江苏南通人,硕士研究生,研究方向为智能信息处理技术;花小朋 ( 1975- ),男,江苏盐城人,博士,副教授,硕士研究生导师,研究方向为智能信息处理技术,通信作者。
更新日期/Last Update: 2023-04-07