[1]朱静,邓艾东,邓敏强,等.基于MED和自适应VMD的行星齿轮箱故障诊断方法[J].东南大学学报(自然科学版),2020,50(4):698-704.[doi:10.3969/j.issn.1001-0505.2020.04.014]
 Zhu Jing,Deng Aidong,Deng Minqiang,et al.Fault diagnosis of planetary gearbox based on minimum entropy deconvolution and adaptive variational mode decomposition[J].Journal of Southeast University (Natural Science Edition),2020,50(4):698-704.[doi:10.3969/j.issn.1001-0505.2020.04.014]
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基于MED和自适应VMD的行星齿轮箱故障诊断方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
50
期数:
2020年第4期
页码:
698-704
栏目:
能源与动力工程
出版日期:
2020-07-20

文章信息/Info

Title:
Fault diagnosis of planetary gearbox based on minimum entropy deconvolution and adaptive variational mode decomposition
作者:
朱静邓艾东邓敏强程强刘洋
东南大学能源与环境学院, 南京 210096; 东南大学火电机组振动国家工程研究中心, 南京 210096
Author(s):
Zhu Jing Deng Aidong Deng Minqiang Cheng Qiang Liu Yang
School of Energy and Environment, Southeast University, Nanjing 210096, China
National Engineering Research Center of Turbo-Generator Vibration, Southeast University, Nanjing 210096, China
关键词:
行星齿轮箱 最小熵反褶积 变分模态分解 故障诊断
Keywords:
planetary gearbox minimum entropy deconvolution(MED) variational mode decomposition(VMD) fault diagnosis
分类号:
TK83
DOI:
10.3969/j.issn.1001-0505.2020.04.014
摘要:
为解决变分模态分解(VMD)在行星齿轮箱故障特征频率提取过程出现的鲁棒性低及分解个数不确定的问题,提出一种基于最小熵反褶积(MED)和自适应变分模态分解(AVMD)的齿轮箱故障诊断方法.首先通过MED对信号进行降噪,突出故障信号特征;采用瞬时频率的新定义及变差概念,自适应选择VMD的级数;使用VMD方法将行星齿轮箱的断齿故障信号分解为若干个本征模态函数(IMF)分量;根据相关系数分析选取带有故障信号的IMF分量,对其进行包络谱分析,以提取故障特征频率.仿真信号和试验信号分析结果表明,使用MED去噪后信号的峰值信噪比提高了10%,解决了传统VMD个数经验选择出现的误差问题从而实现此过程自适应化,解决了VMD在强噪声下针对非线性非平稳信号鲁棒性低的问题,准确提取了风电齿轮箱的故障特征频率.
Abstract:
To solve the problem of low robustness and uncertain decomposition number of variational mode decomposition(VMD)in the fault feature frequency extraction process of planetary gearbox, a gearbox fault diagnosis method based on minimum entropy deconvolution(MED)and adaptive variational mode decomposition(AVMD)was proposed. First, the signal was denoised by the MED to highlight the fault signal characteristics. By using the new definition of the instantaneous frequency and the concept of variation, the series of VMD was adaptively selected. The VMD method was used to decompose the fault signal of the planet gearbox into several intrinsic modal function(IMF)components. According to the analysis of correlation coefficient, the component of IMF with the fault signal was selected to envelope spectrum analysis to extract the fault characteristic frequency. The analysis results of the simulation signal and the experimental signal show that the peak signal-to-noise ratio of the signal is increased by 10% after denoising by using the MED, the error problems of the empirical selection of the number of VMD are solved and the process is self-adaptive. The problem of the low robustness of nonlinear non-stationary signals in the case of the strong noise is solved. The fault characteristic frequency of the wind power gearbox is accurately extracted.

参考文献/References:

[1] Gu Y K, Zhang M, Zhou X Q. Fault diagnosis of gearbox based on improved DUCG with combination weighting method[J]. IEEE Access, 2019(7): 92955-92967. DOI: 10.1109/ACCESS.2019.2927513.
[2] 王况,王科盛,左明健.基于阶次分析技术的行星齿轮箱非平稳振动信号分析[J].振动与冲击,2016,35(5): 140-145. DOI: 10.13465/j.cnki.jvs.2016.05.022.
Wang K, Wang K S, Zuo M J. Fault diagnosis of a planetary gearbox based on order tracking[J]. Journal of Vibration and Shock, 2016, 35(5): 140-145. DOI:10.13465/j.cnki.jvs.2016.05.022. (in Chinese)
[3] Chen X H, Cheng G, Li H Y, et al. Research of planetary gear fault diagnosis based on multi-scale fractal box dimension of CEEMD and ELM[J].Strojni?ki Vestnik-Journal of Mechanical Engineering, 2017, 63(1): 45-55. DOI:10.5545/sv-jme.2016.3811.
[4] 李海平,赵建民,宋文渊.基于EMD-EDT的行星齿轮箱特征提取及状态识别方法研究[J].振动与冲击,2016, 35(3): 48-54. DOI: 10.13465/j.cnki.jvs.2016.03.008.
Li H P, Zhao J M, Song W Y. Method of planetary gearbox feature extraction and condition recognition based on EMD and EDT[J]. Journal of Vibration and Shock, 2016, 35(3): 48-54. DOI:10.13465/j.cnki.jvs.2016.03.008. (in Chinese)
[5] 赵川, 冯志鹏. 多域特征在行星齿轮箱局部故障识别中的应用[J]. 振动与冲击, 2017, 36(18): 56-64. DOI:10.13465/j.cnki.jvs.2017.18.009.
Zhao C, Feng Z P. Application of features extracted from multiple-domain spaces in the localized fault identification of planetary gearboxes[J]. Journal of Vibration and Shock, 2017, 36(18): 56-64. DOI:10.13465/j.cnki.jvs.2017.18.009. (in Chinese)
[6] 何巍, 袁亮, 章翔峰. 改进小波去噪-Teager算子的齿轮微弱故障提取方法[J]. 振动、测试与诊断, 2018, 38(1): 155-161. DOI:10.16450/j.cnki.issn.1004-6801.2018.01.024.
He W, Yuan L, Zhang X F. Weak fault diagnosis method of gearbox based on improved wavelet denoising-Teager energy operator[J]. Journal of Vibration,Measurement & Diagnosis, 2018, 38(1): 155-161. DOI:10.16450/j.cnki.issn.1004-6801.2018.01.024. (in Chinese)
[7] 潘宏侠, 李肖, 李宗贤. 基于S变换的时域边际谱及其应用[J]. 振动.测试与诊断, 2018, 38(1): 39-44. DOI:10.16450/j.cnki.issn.1004-6801.2018.01.006.
Pan H X, Li X, Li Z X. Marginal spectrum based on S transform and its application[J]. Journal of Vibration,Measurement & Diagnosis, 2018, 38(1): 39-44. DOI:10.16450/j.cnki.issn.1004-6801.2018.01.006. (in Chinese)
[8] 李永波, 徐敏强, 赵海洋, 等. 基于层次模糊熵和改进支持向量机的轴承诊断方法研究[J]. 振动工程学报, 2016, 29(1): 184-192. DOI:10.16385/j.cnki.issn.1004-4523.2016.01.023.
Li Y B, Xu M Q, Zhao H Y, et al. A study on rolling bearing fault diagnosis method based on hierarchical fuzzy entropy and ISVM-BT[J]. Journal of Vibration Engineering, 2016, 29(1): 184-192. DOI:10.16385/j.cnki.issn.1004-4523.2016.01.023. (in Chinese)
[9] 郑源, 潘天航, 王辉斌, 等. 改进EMD-ICA去噪在水轮机组隐蔽碰磨诊断中的应用研究[J]. 振动与冲击, 2017, 36(6): 235-240. DOI:10.13465/j.cnki.jvs.2017.06.037.
Zheng Y, Pan T H, Wang H B, et al. Improved EMD-ICA method used in the hidden rubbing fault diagnosis of turbine units[J]. Journal of Vibration and Shock, 2017, 36(6): 235-240. DOI:10.13465/j.cnki.jvs.2017.06.037. (in Chinese)
[10] Dragomiretskiy K, Zosso D. Variational mode decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3):531-544. DOI: 10.1109/TSP.2013.2288675.
[11] Huang N E, Shen S S P. Hilbert-Huang transform and its applications[M]// Interdisciplinary Mathematical Sciences. Singapore: World Scientific Publishing Co. Pte. Ltd., 2005, 5: 227-262. DOI: 10.1142/9789812703347_0011.
[12] Ooe M, Ulrych T J. Minimum entropy deconvolution with an exponential transformation[J]. Geophysical Prospecting, 1979, 27(2): 458-473. DOI: 10.1111/j.1365-2478.1979.tb00979.x.

相似文献/References:

[1]朱静,邓艾东,邓敏强,等.基于RSIFICA的行星齿轮箱故障诊断方法[J].东南大学学报(自然科学版),2020,50(2):377.[doi:10.3969/j.issn.1001-0505.2020.02.023]
 Zhu Jing,Deng Aidong,Deng Minqiang,et al.Fault diagnosis method of planetary gear box based on RSIFICA[J].Journal of Southeast University (Natural Science Edition),2020,50(4):377.[doi:10.3969/j.issn.1001-0505.2020.02.023]

备注/Memo

备注/Memo:
收稿日期: 2019-11-25.
作者简介: 朱静(1993—),女,博士生;邓艾东(联系人),男,博士,教授,博士生导师,dnh@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(51875100)、中央高校基本科研业务费专项资金资助项目(2242020k30031).
引用本文: 朱静,邓艾东,邓敏强,等.基于MED和自适应VMD的行星齿轮箱故障诊断方法[J].东南大学学报(自然科学版),2020,50(4):698-704. DOI:10.3969/j.issn.1001-0505.2020.04.014.
更新日期/Last Update: 2020-07-20