Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy

Fuming Zhou; Jinxing Shen; Xiaoqiang Yang; Wuqiang Liu; Xiaolin Liu

doi:10.16578/j.issn.1004.2539.2021.04.019

您当前的位置：

首页 >

文章列表页 >

Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy

Test·Analysis | 更新时间：2022-11-10

- Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy
- Journal of Mechanical Transmission Vol. 45, Issue 4, Pages: 112-122(2021)
- 作者机构：
  
  1.陆军工程大学野战工程学院，江苏南京 210001
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2021.04.019
  CLC：
扫描看全文
周付明,申金星,杨小强等.基于改进多元多尺度色散熵的齿轮箱多通道振动信号故障诊断[J].机械传动,2021,45(04):112-122.

Zhou Fuming,Shen Jinxing,Yang Xiaoqiang,et al.Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy[J].Journal of Mechanical Transmission,2021,45(04):112-122.
周付明,申金星,杨小强等.基于改进多元多尺度色散熵的齿轮箱多通道振动信号故障诊断[J].机械传动,2021,45(04):112-122. DOI： 10.16578/j.issn.1004.2539.2021.04.019.

Zhou Fuming,Shen Jinxing,Yang Xiaoqiang,et al.Fault Diagnosis of Gearbox Multi-channel Vibration Signal based on Improved Multivariate Multiscale Dispersion Entropy[J].Journal of Mechanical Transmission,2021,45(04):112-122. DOI： 10.16578/j.issn.1004.2539.2021.04.019.

摘要

齿轮箱发生故障时，其振动信号具有不平稳和非线性等特征，而常用的齿轮箱故障诊断方法大多是建立在单通道振动信号分析基础上，容易造成故障信息丢失，故而在工业生产中实用性受限。为了克服此缺陷，将多元多尺度色散熵引入到齿轮箱故障诊断当中，并改进其粗粒化方式，提出了改进多元多尺度色散熵，用以提取齿轮箱多通道振动信号的故障信息。在此基础上，提出一种基于集合经验模态分解，改进多元多尺度色散熵和遗传算法优化支持向量机的齿轮箱故障诊断方法。通过实验数据分析，并与多元多尺度样本熵、多元多尺度模糊熵等现有方法相比较，证明该方法具有更高的准确率和稳定性，且在处理短时间序列时具有明显优势。

Abstract

When the gearbox fails， its vibration signal is unstable and nonlinear. The commonly applied gearbox fault diagnosis methods are almost all based on the single-channel vibration signal analysis，which is easy to cause the loss of fault information，so the practicality in industrial production is limited. In order to overcome this defect， the multivariate multiscale dispersion entropy is introduced into the gearbox fault diagnosis. Meanwhile， the coarse graining method of it is improved， and improved multivariate multiscale dispersion entropy（IMMDE） is proposed to extract fault information of multi-channel vibration signal of gearbox. Based on this，a new gearbox fault diagnosis method based on ensemble empirical mode decomposition （EEMD），IMMDE and genetic algorithm optimization support vector machine（GA-SVM） is proposed. Through the analysis of experimental data， it can be seen that this method has higher accuracy and stability compared with multivariate multiscale sample entropy（MMSE） and multivariate multiscale fuzzy entropy （MMFE），and has obvious advantages in dealing with short time series.

关键词

齿轮箱故障诊断集合经验模态分解改进多元多尺度色散熵遗传算法优化支持向量机

Keywords

GearboxFault diagnosisEEMDImproved multivariate multiscale dispersion entropyGA-SVM

references

LIANG X，ZUO M J，FENG Z.Dynamic modeling of gearbox faults：a review［J］.Mechanical Systems and Signal Processing，2018，98（1）：852-876.

徐甜甜，孙文磊，王宏伟，等.VMD与谱峭度法在齿轮箱故障诊断中的应用［J］.机械科学与技术，2019：1-5［2020-03-19］.

XU Tiantian，SUN Wenlei，WANG Hongwei，et al.Application of variational mode decomposition and spectral kurtosisin gear box fault diagnosis［J］.Mechanical Science and Technology for Aerospace Engineering，2019：1-5［2020-03-19］.

李林峰，赵军，郭天太，等.基于EEMD、模糊熵和SVM的齿轮故障诊断方法［J］.机械传动，2014，38（2）：147-151.

LI Linfeng，ZHAO Jun，GUO Tiantai，et al.Gear fault diagnosis based on EEMD，Fuzzy Entropy and SVM［J］.Journal of Mechanical Transmission，2014，38（2）：147-151.

NIKULIN V V，BRISMAR T.Comment on multiscale entropy analysis of complex physiologic time series［J］.Physical Review Letters，2004，92（8）：089803.

杨文志，邸志强，邸志刚.基于VMD与多尺度排列熵的滚动轴承故障诊断［J］.技术与市场，2019，26（8）：82-83.

YANG Wenzhi，DI Zhiqiang，DI Zhigang.Fault diagnosis of rolling bearing based on VMD and Multi-scale Permutation Entropy［J］.Technology and Market，2019，26（8）：82-83.

戴邵武，陈强强，戴浩然，等.基于MFE-GASVM的机载燃油泵故障诊断［J］.计算机测量与控制，2020，28（1）：8-10.

DAI Shaowu，CHEN Qiangqiang，DAI Haoran，et al.Airborne fuel pumps fault diagnosis based on MFE-GASVM［J］.Computer Measurement and Control，2020，28（1）：8-10.

WEI Y，XU M，LI Y，et al.A feature extraction method based on ICD and MSE for gearbox［J］.Journal of Vibroengineering，2016，18（6）：3596-3607.

郑近德，陈敏均，程军圣，等.多尺度模糊熵及其在滚动轴承故障诊断中的应用［J］．振动工程学报，2014，27（1）：145-151．

ZHENG Jinde，CHEN Minjun，CHENG Junsheng，et al．Multiscale fuzzy entropy and its application in rolling bearing fault diagnosiss ［J］.Journal of Vibration Engineering，2014，27（1）：145-151．

郑近德，代俊习，朱小龙，等.基于改进多尺度模糊熵的滚动轴承故障诊断方法［J］.振动、测试与诊断，2018，38（5）：929-934.

ZHENG Jinde，DAI Junxi，ZHU Xiaolong，et al.A rolling bearing fault diagnosis approach based on improved multiscale fuzzy entropy ［J］.Journal of Vibration，Measurement and Diagnosis，2018，38 （5）：929-934.

ROSTAGHI M，AZAMI H.Dispersion entropy：a measure for time-series analysis［J］.IEEE Signal Processing Letters，2016，23（5）：610-614.

AZAMI H，KINNEY-LANG E，EBIED A，et al.Multiscale dispersion entropy for the regional analysis of resting-state magnetoencephalogram complexity in Alzheimer's disease［C］//Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society （EMBC），July 11-15，2017，Jeju，Korea（South）.New York：IEEE，2017：3182-3185.

雷亚国，林京，何正嘉.基于多传感器信息融合的行星齿轮箱故障诊断［C］//第十二届全国设备故障诊断学术会议论文集，2010年8月15日，中国，辽宁，沈阳.上海：《振动与冲击》编辑部，2010：222-224.

LEI Yaguo，LIN Jing，HE Zhengjia.Planetary gearbox fault diagnosis based on multi-sensor information fusion［C］//Proceedings of the 12th National Equipment Fault Diagnosis Academic Conference，August 15，2010，Shenyang，Liaoning，China.Shanghai：Editorial Office of Vibration and Shock，2010：222-224.

WANG X，SI S，LI Y，et al.An integrated method based on refined composite multivariate hierarchical permutation entropy and random forest and its application in rotating machinery［J］.Journal of Vibration and Control，2020，26（3/4）：146-160.

李鹏，刘澄玉，李丽萍，等.多尺度多变量模糊熵分析［J］.物理学报，2013，62（12）：122-130.

LI Peng，LIU Chengyu，LI Liping，et al.Multiscale multivariate fuzzy entropy analysis［J］.Acta Physica Sinica，2013，62（12）：122-130．

AHMED M U，MANDIC D P.Multivariate multiscale entropy analysis［J］.IEEE Signal Processing Letters，2011，19（2）：91-94.

AHMED M U，MANDIC D P.Multivariate multiscale entropy：a tool for complexity analysis of multichannel data［J］.Physical Review E，2011，84（1）：061918.

AHMED M U，CHANWIMALUEANG T，THAYYIL S，et al.A multivariate multiscale fuzzy entropy algorithm with application to uterine EMG complexity analysis［J］.Entropy，2016，19（1）：2.

AZAMI H，FERNANDEZ A，ESCUDERO J.Multivariate multiscale dispersion entropy of biomedical times series［J］.Entropy，2019，21（9）：913-933.

WU S D，WU C W，LIN S G，et al.Time series analysis using composite multiscale entropy［J］.Entropy，2013，15（3）：1069-1084.

AZAMI H，ESCUDERO J.Amplitude-and fluctuation-based dispersion entropy［J］.Entropy，2018，20（3）：210.

YAN X，JIA M.Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection［J］.Knowledge-Based Systems，2019，163：450-471.

COSTA M，GOLDBERGER A L，PENG C K.Multiscale entropy analysis of complex physiologic time series［J］.Physical Review Letters，2002，89（6）：068102.

郑近德，潘海洋，张俊，等.基于多变量多尺度模糊熵的行星齿轮箱故障诊断［J］.振动与冲击，2019，38（6）：187-193.

ZHENG Jinde，PAN Haiyang，ZHANG Jun，et al.Multivariate multiscale fuzzy entropy based planetary gearbox fault diagnosis［J］.Journal of Vibration and Shock，2019，38（6）：187-193.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Gearbox Fault Diagnosis Based on the LMD Cloud Model and PSO-KELM

Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy

Gearbox Fault Diagnosis based on GAF-inceptionResNet

Gearbox Fault Diagnosis based on Time-frequency Combination Feature Extraction and Manifold Learning of MS-LTSA

Fault Diagnosis of Wind Turbine Gearbox based on Signal Model and Order Analysis

Related Author

No data

Related Institution

School of Mechanical and Electrical Engineering, Xi'an Polytechnic University

Engineering Training Center, Jiangsu Normal University

School of Mechatronic Engineering, China University of Mining and Technology

Department of Information Technology， Shanxi Professional College of Finance

College of Mechanical and Vehicle Engineering，Taiyuan University of Technology

⁰