基于CEEMDAN-DRT的滚动轴承故障诊断方法研究

别锋锋; 谷晟; 庞明军; 郭越; 杨罡

doi:10.16578/j.issn.1004.2539.2020.04.025

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基于CEEMDAN-DRT的滚动轴承故障诊断方法研究

开发应用 | 更新时间：2022-10-20

- 基于CEEMDAN-DRT的滚动轴承故障诊断方法研究
- Research of Fault Diagnosis Method of Rolling Bearing based on CEEMDAN-DRT
- 机械传动 2020年44卷第4期页码：158-164
- 作者机构：
  
  1.常州大学机械工程学院，江苏常州 213164
- 作者简介：
  
  别锋锋（1979— ），男，湖北仙桃人，博士后，副教授，主要研究向为机械设备状态检测与故障诊断，振动信号处理与分析，石油石化备安全、完整性评价。
- 基金信息：
  
  国家自然科学基金(51376026┫江苏省高等学校自然科学研究重大项目┣19KJA430004)
- DOI：10.16578/j.issn.1004.2539.2020.04.025
  中图分类号：
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别锋锋,谷晟,庞明军等.基于CEEMDAN-DRT的滚动轴承故障诊断方法研究[J].机械传动,2020,44(04):158-164.

Bie Fengfeng Gu Sheng Pang Mingjun Guo Yue Yang Gang.Research of Fault Diagnosis Method of Rolling Bearing based on CEEMDAN-DRT[J].Journal of Mechanical Transmission,2020,44(04):158-164.
别锋锋,谷晟,庞明军等.基于CEEMDAN-DRT的滚动轴承故障诊断方法研究[J].机械传动,2020,44(04):158-164. DOI： 10.16578/j.issn.1004.2539.2020.04.025.

Bie Fengfeng Gu Sheng Pang Mingjun Guo Yue Yang Gang.Research of Fault Diagnosis Method of Rolling Bearing based on CEEMDAN-DRT[J].Journal of Mechanical Transmission,2020,44(04):158-164. DOI： 10.16578/j.issn.1004.2539.2020.04.025.

摘要

针对滚动轴承故障信息不易提取的特性，提出了完全集合经验模态分解（CEEMDAN）自适应消噪和共振解调技术（DRT）相结合的故障诊断方法。首先，利用CEEMDAN自适应地将信号分解成多个分量，通过互相关系数方法进行重构以达到消噪的目的；然后，对重构的信号进行谱峭度分析，得到冲击成分所在的频带，并据此设计带通滤波器对重构信号进行滤波处理；最后，对滤波后的信号进行Hilbert包络谱分析，提取冲击成分的频率，并与滚动轴承故障特征频率对比，进行故障模式识别。通过动力学仿真和滚动轴承实验对该方法进行了有效性论证。结果表明，该方法可以有效识别滚动轴承的故障信息。

Abstract

Aiming at the feature extraction for the rolling bearing，a fault diagnosis method based on CEEMDAN adaptive denoising combining with DRT （demodulated resonance technology） is presented.Firstly，the original vibration signal is decomposed into several components with CEEMDAN adaptively，and the reconstruction is performed on regarding the correlation coefficient method to realize the purpose of eliminating noise.Then，the reconstructed signal is analyzed by spectral kurtosisto to achieve the frequency band of the impact component.Based on this，a bandpass filter is designed for the reconstructed signal.Finally，the filtered signals are analyzed by energy Hilbert envelope spectrum.With reference on the characteristic frequency of the rolling bearing failure modes，the pattern of the bearing is recognized.The effectiveness of the method is demonstrated by dynamics simulation and rolling bearing experiments.The result shows that the method can be used to identify the fault information of the rolling bearings effectively.

关键词

滚动轴承 CEEMDAN DRT 故障诊断

Keywords

Rolling bearingCEEMDANDRTFault diagnosis

references

时培明，许帅，李培.基于小波去噪和EEMD包络解调分析的滚动轴承故障诊断方法[J].现代制造工程，2015（12）:12-17.

SHI Peiming，XU Shuai，LI Pei.Study on rolling element bearing faults diagnosis based on wavelet de-noising technique and EEMD envelope demodulation analysis[J].Modern Manufacturing Engineering，2015（12）:12-17.

SINGH J，DARPE A K，SINGH S P.Bearing damage assessment using Jensen-Rényi Divergence based on EEMD[J].Mechanical Systems & Signal Processing，2016，87:307-339.

刘觉晓.基于EEMD的滚动轴承振动故障特征提取与诊断研究[D].保定：华北电力大学，2015:16-17.

LIU Juexiao .Research on extraction and diagnosis of fault feature of vibration of rolling bearing based on EEMD[D].Baoding: North China Electric Power University，2015:16-17.

DAVID L D，JAIN M J.Ideal spatial adaptation by wavelet shrinkage[J].Biometrika，1994（81）:425-455.

TORRS ME，COLOMINAS MA，SCHLOTTHAUER G，er al .Flandrin P.A complete ensemble empirical mode decomposition with adaptive noise[C].Proceedings of the IEEE International Conference on Acoustics，Speech and Signal Processing，2011:4144-4147.

HARTING D，TAYLOR J.Demodulated resonance analysis system：US3842663[P].1974-10-22.

俞培松.滚动轴承振动故障诊断技术的研究及其实际应用[D].上海：同济大学，2007:7-10.

YU Peisong.Research on vibration diagnosis technology of rolling bearing and its practical application[D].Shanghai:Tongji University，2007:7-10.

欧森火.基于Hilbert-Huang变换的机械故障诊断的研究[D].北京：北京邮电大学，2010:31-32.

OU Senhuo.Research on mechanical fault diagnosis based on hilbert-huang transform[D].Beijing:Beijing University of Posts and Telecommunications，2010:31-32.

郭艳平，龙涛元.振动信号模型在滚动轴承故障诊断中的应用[J].机械设计与制造，2018（1）:270-272.

GUO Yanping，LONG Taoyuan.Application of vibration signal model in rolling bearing fault diagnosis[J].Mechanical Design & Manufacturing，2018（1）:270-272.

GUO D H，WNA S T，LV Z J，et al.The analysis of gearbox fault diagnosis research based on the EMD and Hilbert envelope demodulation[J].Advanced Materials Research，2014，3181:1800-1805.

刘佩森.基于共振解调理论的滚动轴承故障诊断仪研究[D].成都:电子科技大学，2014:21-31.

LIU Peisen.Research on fault diagnosis instrument of rolling bearing based on the theory of resonance demodulation[D].Chengdu:University of Electronic Science and Technology of China，2014:21-31.

BESSAM B，MENACER A，BOUMEHRAZ M.DWT and Hilbert transform for broken rotor bar fault diagnosis in induction machine at low load[J].Energy Procedia，2015:1248-1257.

施莹，庄哲，林建辉.基于EEMD排列熵的高速列车轮对轴承故障诊断方法[J].中国测试，2017（11）:97-103.

SHI Ying，ZHUANG Zhe，LIN Jianhui.Fault diagnosis method of high-speed train axle bearing based on EEMD permutation entropy[J].China Test，2017（11）:97-103.

何刘，丁建明，林建辉.完全互补小波噪声辅助集总经验模态分解[J].振动与冲击，2017，36（4）：232-242.

HE Liu，DING Jianming，LIN Jianhui.A complete complementary wavelet ensemble empirical mode decomposition with adaptive noise[J].Journal of Vibration & Shock，2017，36（4）:232-242.

吴小涛，杨锰，袁晓辉，等.基于峭度准则EEMD及改进形态滤波方法的轴承故障诊断[J].振动与冲击，2015，34（2）:38-44.

WU Xiaotao，YANG Meng，YUAN Xiaohui，et al.Bearing fault diagnosis using EEMD and improved morphological filtering method based on kurtosis criterion[J].Journal of Vibration and Shock，2015，34（2）:38-44.

石文磊，陈兴明，袁海龙.基于EMD和Hilbert包络谱的滚动轴承故障诊断[J].机械工程与自动化，2010（5）:108-110.

SHI WenLei，CHEN XingMing，YUAN HaiLong.Fault diagnosis of rolling bearings based on EMD and Hilbert envelope spectrum[J].Mechanical Engineering & Automation，2010（5）:108-110.

李长健，向立明，刘永强，等.基于ADAMS的高速机车双列圆锥滚子轴承典型故障仿真分析[J].轴承，2018（6）:55-59.

LI Changjian，XIANG Liming，LIU Yongqiang，et al.Simulation analysis on double row tapered roller bearings with typical faults in high-speed locomotive based on ADAMS[J].Bearing，2018（6）:55-59.

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