Parameter Optimized Variational Mode Decomposition Method with Application to Incipient Fault Diagnosis of Rolling Bearing

doi:10.7652/xjtuxb201505012

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Parameter Optimized Variational Mode Decomposition Method with Application to Incipient Fault Diagnosis of Rolling Bearing

更新时间：2025-07-09

- Parameter Optimized Variational Mode Decomposition Method with Application to Incipient Fault Diagnosis of Rolling Bearing
- Vol. 49, Issue 5, Pages: 73-81(2015)
- 作者机构：
  
  华北电力大学能源动力与机械工程学院,河北,保定,071000
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201505012
  CLC： TH17
- Online First：10 May 2015，
  
  Published：2015
- 稿件说明：
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Parameter Optimized Variational Mode Decomposition Method with Application to Incipient Fault Diagnosis of Rolling Bearing[J]. 2015, 49(5): 73-81.
DOI：

Parameter Optimized Variational Mode Decomposition Method with Application to Incipient Fault Diagnosis of Rolling Bearing[J]. 2015, 49(5): 73-81. DOI： 10.7652/xjtuxb201505012.

摘要

针对滚动轴承早期故障特征提取困难的问题

提出一种基于参数优化变分模态分解的轴承早期故障诊断方法。首先利用粒子群优化算法对变分模态分解算法的最佳影响参数组合进行搜索

搜索结束后根据所得结果设定变分模态分解算法的惩罚参数和分量个数

并利用参数优化变分模态分解算法对故障信号进行处理。原故障信号经过处理后被分解为若干本征模态函数分量

由此筛选出最佳信号分量并进行包络解调运算

最终通过分析信号的包络谱可判断轴承的故障类型。利用参数优化变分模态分解方法对轴承故障仿真和实测信号进行分析

均成功提取出微弱特征频率信息

表明参数优化变分模态分解方法可实现滚动轴承早期故障的有效判别

具有一定的可靠性和应用价值。

Abstract

The fault feature of rolling bearing in early failure period is difficult to extract. An incipient fault diagnosis method for rolling bearing based on parameter optimized variational mode decomposition method was proposed. Particle swarm optimization algorithm was used to search for the best combination of influencing parameters of variational mode decomposition algorithm

the penalty parameter and number of components were then set according to the searching results

and the fault signal was processed by parameter optimized variational mode decomposition algorithm. The original fault signal was decomposed into several intrinsic mode function components. The best signal component was selected and processed by envelope demodulation algorithm

the fault type of bearing was judged by analyzing the envelope spectrum of the signal. The simulated and measured signals of fault bearing were analyzed by parameter optimized variational mode decomposition method and the weak characteristic frequency information was extracted successfully. The results show that the proposed method enables to judge the incipient fault of rolling bearing effectively with desired reliability.

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references

梅检民, 肖云魁, 贾继德, 等. 基于改进阶比的变速器微弱故障特征提取 [J]. 振动工程学报, 2012, 25(3): 317-322.

MEI Jianmin, XIAO Yunkui, JIA Jide, et al. Weak fault characteristics extraction for automobile transmission based on improved order analysis [J]. Journal of Vibration Engineering, 2012, 25(3): 317-322.

冯辅周, 司爱威, 饶国强, 等. 基于小波相关排列熵的轴承早期故障诊断技术 [J]. 机械工程学报, 2012, 48(13): 73-79.

FENG Fuzhou, SI Aiwei, RAO Guoqiang, et al. Early fault diagnosis technology for bearing based on wavelet correlation permutation entropy [J]. Journal of Mechanical Engineering, 2012, 48(13): 73-79.

HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. Proceedings of the Royal Society: A, 1998(454): 903-993.

DU Qiuhua, YANG Shunian. Application of the EMD method in the vibration analysis of ball bearings [J]. Mechanical Systems and Signal Processing, 2007, 21(6): 2634-2644.

程军圣, 于德介, 杨宇. 基于EMD的能量算子解调方法及其在机械故障诊断中的应用 [J]. 机械工程学报, 2004, 40(8): 115-118.

CHENG Junsheng, YU Dejie, YANG Yu. Energy operator demodulating approach based on EMD and its application in mechanical fault diagnosis [J]. Journal of Mechanical Engineering, 2004, 40(8): 115-118.

李辉, 郑海起, 唐立伟. 声测法和经验模态分解在轴承故障诊断中的应用 [J]. 中国电机工程学报, 2006, 26(15): 124-128.

LI Hui, ZHENG Haiqi, TANG Liwei. Application acoustic emission and empirical mode decomposition to faults diagnosis of bearing [J]. Proceedings of the CSEE, 2006, 26(15): 124-128.

FLANDRIN P, RILLING G, GONCALVES P. Empirical mode decomposition as a filter band [J]. IEEE Signal Processing Letters, 2004, 11(2): 112-114.

DRAGOMIRETSKIY K, ZOSSO D. Variational mode decomposition [J]. IEEE Transactions on Signal Processing, 2014, 62(3): 531-544.

KENNEDY J, EBERHART R C. Particle swarm optimization [C]∥IEEE International Conference on Neural Networks. Piscataway, NJ, USA: IEEE, 1995: 1942-1948.

沈伋, 韩丽川, 沈益斌. 基于粒子群算法的飞机总体参数优化 [J]. 航空学报, 2008, 29(6): 1538-1541.

SHEN Ji, HAN Lichuan, SHEN Yibin. Optimization of airplane primary parameters based on particle swarm algorithm [J]. Acta Aeronautica et Astronautica Sinica, 2008, 29(6): 1538-1541.

李宁. 粒子群优化算法的理论分析与应用研究 [D]. 武汉: 华中科技大学, 2006.

蒋永华, 汤宝平, 刘文艺, 等. 基于参数优化Morlet小波变换的故障特征提取方法 [J]. 仪器仪表学报, 2010, 31(1): 56-60.

JIANG Yonghua, TANG Baoping, LIU Wenyi, et al. Feature extraction method based on parameter optimized Morlet wavelet transform [J]. Chinese Journal of Scientific Instrument, 2010, 31(1): 56-60.

王宏超, 陈进, 董广明. 基于最小熵解卷积与稀疏分解的滚动轴承微弱故障特征提取 [J]. 机械工程学报, 2013, 49(1): 88-94.

WANG Hongchao, CHEN Jin, DONG Guangming. Fault diagnosis method for rolling bearing's weak fault based on minimum entropy deconvolution and sparse decomposition [J]. Journal of Mechanical Engineering, 2013, 49(1): 88-94.

LIN J, ZUO M J, FYFE K R. Mechanical fault detection based on the wavelet de-noising technique [J]. Journal of Vibration and Acoustics, 2004, 126: 9-16.

田福庆,罗荣,李万,等.改进的卷积型小波包分解及在故障诊断中的应用.2014,48(3):89-95.[doi:10.7652/xjtuxb 201403017]

杨清宇,孙凤伟.一种迭代改进的球向量机故障诊断算法.2013,47(10):1-6.[doi:10.7652/xjtuxb201310001]

夏虎,庄健,于德弘.面向高维特征故障数据的进化软子空间聚类算法.2013,47(5):115-120.[doi:10.7652/xjtuxb2013 05021]

胡小秋,陈维福.角接触球轴承热特性分析及试验.2015,49(2):106-110.[doi:10.7652/xjtuxb201502018]

周子超,王伊卿,吴文武,等.机床主轴轴承热诱导预紧力及刚度计算与实验研究.2015,49(2):111-116.[doi:10.7652/xjtuxb201502019]

金海善,朱爱斌,陈渭.利用改进牛顿-拉夫逊法的高速圆柱滚子轴承打滑分析.2015,49(1):133-138.[doi:10.7652/xjtuxb201501022]

位文明,吕盾,张俊,等.转台轴承静刚度建模及其影响因素分析.2014,48(12):8-14.[doi:10.7652/xjtuxb201412002]

翟强,闫柯,张优云,等.高速角接触球轴承腔内气相流动与传热特性研究.2014,48(12):29-33.[doi:10.7652/xjtuxb 201412005]

陈汝刚,陈韬.温度影响下箔片动压止推轴承分析.2014,48(11):32-36.[doi:10.7652/xjtuxb201411006]

李建栋,朱永生,熊青青,等.定压预紧主轴轴向动态刚度特性研究.2014,48(10):126-130.[doi:10.7652/xjtuxb2014 10020]

易均,刘恒,刘意,等.歪斜安装对组配轴承转子系统动力学特性影响.2014,48(9):107-111.[doi:10.7652/xjtuxb201409 018]

耿涛,孟庆丰,贾谦,等.薄衬层结构滑动轴承润滑膜厚度的超声检测方法.2014,48(8):80-85.[doi:10.7652/xjtuxb 201408014]

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