[1]别锋锋,郭 越,谷 晟,等.改进型ESMD在齿轮箱轴承故障诊断中的应用[J].常州大学学报(自然科学版),2021,33(03):32-41.[doi:10.3969/j.issn.2095-0411.2021.03.005]
　BIE Fengfeng,GUO Yue,GU Sheng,et al.Application Research of Improved ESMD on Fault Diagnosis Method for Gearbox Bearings[J].Journal of Changzhou University(Natural Science Edition),2021,33(03):32-41.[doi:10.3969/j.issn.2095-0411.2021.03.005]
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改进型ESMD在齿轮箱轴承故障诊断中的应用()
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常州大学学报(自然科学版)[ISSN:2095-0411/CN:32-1822/N]

卷:
第33卷
期数:
2021年03期
页码:
32-41
栏目:
机械制造及其自动化
出版日期:
2021-05-28

文章信息/Info

Title:
Application Research of Improved ESMD on Fault Diagnosis Method for Gearbox Bearings
文章编号:
2095-0411(2021)03-0032-10
作者:
别锋锋;  郭 越;  谷 晟;  裴峻峰;  庞明军
(常州大学 机械与轨道交通学院, 江苏 常州 213164)
Author(s):
BIE Fengfeng;  GUO Yue;  GU Sheng;  PEI Junfeng;  PANG Mingjun
(School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou 213164, China)
关键词:
滚动轴承;  模态分解;  共振解调技术;  故障诊断
Keywords:
rolling bearing;  mode decomposition;  demodulated resonance technology;  fault diagnosis
分类号:
TH 113.1; TH 17
DOI:
10.3969/j.issn.2095-0411.2021.03.005
文献标志码:
A
摘要:
针对如何有效提取齿轮箱滚动轴承故障信息, 提出了一种改进型极值点对称模态分解(IESMD)自适应消噪与共振解调技术(DRT)相结合的诊断方法。该方法首先利用IESMD对原始滚动轴承信号进行自适应分解成多个IMF分量; 接着通过互相关系数方法对信号进行重构以达到消噪的目的; 然后对重构信号进行谱峭度分析, 通过冲击成分所在频带范围设计带通滤波器实现对重构信号的滤波处理; 最后将滤波后的信号进行Teager能量谱分析, 求出其瞬时幅值, 并对瞬时幅值进行频谱分析, 得到高频共振信号的能量谱, 对比故障特征频率进行滚动轴承的故障模式识别。通过动力学仿真和齿轮箱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齿轮箱中滚动轴承的故障信息。
Abstract:
Aiming at the feature extraction for the rolling bearing in gearbox, a fault diagnosis method based on improved extreme-point symmetric mode decomposition(IESMD)adaptive denoising combining with demodulated resonance technology(DRT)is presented. Firstly, the original vibration signal is decomposed into several components with IESMD adaptively, and the reconstruction is performed regarding the correlation coefficient method to realize the noise eliminating; 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 Teager energy spectrum. With reference on the characteristic frequency of the rolling bearing failure modes, the patterns of the bearing are recognized. The effectiveness of the method is demonstrated by the dynamic simulation and experimental extraction of the fault signal of the gear box rolling bearing. The results show that the method can effectively identify the fault information of the gear box rolling bearing.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2020-12-09。
基金项目:国家自然科学基金资助项目(51376026); 江苏省高等学校自然科学研究重大项目(19KJA430004); 江苏省研究生科研与实践创新计划项目(SJCX19_0662)。
作者简介:别锋锋(1979—), 男, 湖北仙桃人, 博士, 副教授。 E-mail:fengf721@sina.com
更新日期/Last Update: 1900-01-01