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

作　　者：周杰[1,2] 王云艺 陈传海 王立鼎[2,3] 刘阔 ZHOU Jie;WANG Yun-yi;CHEN Chuan-hai;WANG Li-ding;LIU Kuo(Key Laboratory of CNC Equipment Reliability,Ministry of Education,Jilin University,Changchun 130022,China;College of Mechanical and Aerospace Engineering,Jilin University,Changchun 130022,China;School of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China)

机构地区：[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

出　　处：《吉林大学学报（工学版）》2022年第2期450-457,共8页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(51975249);重庆市自然科学基金项目(cstc2021jcyj-msxm2142).

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。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.

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 

分 类 号：TH132.41[机械工程—机械制造及自动化]