基于改进MED⁃SSD的齿轮箱复合故障诊断方法

doi:10.13229/j.cnki.jdxbgxb20211139

吉林大学学报(工学版) ›› 2022, Vol. 52 ›› Issue (2): 450-457.doi: 10.13229/j.cnki.jdxbgxb20211139

• 车辆工程·机械工程 • 上一篇

基于改进MED⁃SSD的齿轮箱复合故障诊断方法

周杰^1,²( ),王云艺²,陈传海^1,²( ),王立鼎^2,³,刘阔³

^1.吉林大学数控装备可靠性教育部重点实验室，长春 130022
^2.吉林大学机械与航空航天工程学院，长春 130022
^3.大连理工大学机械工程学院，辽宁大连 116024

收稿日期:2021-10-29 出版日期:2022-02-01 发布日期:2022-02-17
通讯作者: 陈传海 E-mail:zj_zhongb@163.com;cchchina@foxmail.com
作者简介:周杰（1994-），男，博士研究生.研究方向：故障诊断.E-mail：zj_zhongb@163.com
基金资助:
国家自然科学基金项目(51975249);重庆市自然科学基金项目(cstc2021jcyj-msxm2142)

Gearbox complex fault diagnosis method based on improved minimum entropy deconvolution and singular spectrum decomposition

Jie ZHOU^1,²(),Yun-yi WANG²,Chuan-hai CHEN^1,²( ),Li-ding WANG^2,³,Kuo LIU³

^1.Key Laboratory of CNC Equipment Reliability，Ministry of Education，Jilin University，Changchun 130022，China
^2.College of Mechanical and Aerospace Engineering，Jilin University，Changchun 130022，China
^3.School of Mechanical Engineering，Dalian University of Technology，Dalian 116024，China

Received:2021-10-29 Online:2022-02-01 Published:2022-02-17
Contact: Chuan-hai CHEN E-mail:zj_zhongb@163.com;cchchina@foxmail.com

摘要/Abstract

摘要：

针对齿轮箱在强噪声环境下复合故障信号微弱、故障特征难以提取等问题，本文提出了一种改进的最小熵反褶积（MED）与奇异谱分解（SSD）结合的方法。首先，构建边际功率谱峰度指数（MPSK），利用MPSK对MED进行参数优化；为弥补SSD的不足，将改进的MED作为SSD的前置滤波器；然后利用相关系数分析法选择有意义的奇异谱分量（SSC）；最后对信号进行频谱分析，确定具体的故障模式。采用仿真信号与齿轮箱试验台的复合故障信号对所提方法进行了应用，验证了方法的有效性和优越性。

关键词: 奇异谱分解, 最小熵反褶积, 原子搜索优化算法, 模态分量重构, 复合故障

Abstract:

Aiming at the problems of weak Complex fault signal and difficult to extract fault features of gearbox in strong noise environment， an improved minimum entropy deconvolution（MED） combined with singular spectrum decomposition（SSD） is proposed to extract fault features. Firstly， margin and power spectrum kurtosis（MPSK） index is constructed to optimize the parameters of MED； Secondly， the improved MED is used as the pre-filter of SSD to make up for the deficiency of SSD； Then the meaningful SSC components are selected by correlation coefficient analysis； Finally， the signal spectrum is analyzed to determine the fault characteristics. The effectiveness and superiority of the proposed method are verified by the Complex fault signal of simulation signal and gearbox test-bed.

Key words: singular spectrum decomposition, minimum entropy deconvolution, atom search optimization, combined mode function, complex fault

中图分类号:

TH132.41

周杰,王云艺,陈传海,王立鼎,刘阔. 基于改进MED⁃SSD的齿轮箱复合故障诊断方法[J]. 吉林大学学报(工学版), 2022, 52(2): 450-457.

Jie ZHOU,Yun-yi WANG,Chuan-hai CHEN,Li-ding WANG,Kuo LIU. Gearbox complex fault diagnosis method based on improved minimum entropy deconvolution and singular spectrum decomposition[J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(2): 450-457.

图/表 8

参考文献 19

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分量	CC值
SSC1	0.0214
SSC2	0.1826
SSC3	0.2935
SSC4	0.3846
SSC5	0.5012

分量	CC值	分量	CC值
SSC1	0.1632	SSC5	0.3762
SSC2	0.0053	SSC6	0.1265
SSC3	0.0368	SSC7	0.0039
SSC4	0.4326

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基于改进MED⁃SSD的齿轮箱复合故障诊断方法

Gearbox complex fault diagnosis method based on improved minimum entropy deconvolution and singular spectrum decomposition

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