排列熵优化改进变模态分解算法诊断齿轮箱故障  

Gearbox fault diagnosis based on permutation entropy optimized variational mode decomposition

作　　者：王志坚 常雪 王俊元[1] 杜文华[1] 段能全[1] 党长营 Wang Zhijian;Chang Xue;Wang Junyuan;Du Wenhua;Duan Nengquan;Dang Changying(College of Mechanical Engineering,North University of China,Taiyuan 030051,China;College of Mechanical Engineering,Chongqing University,Chongqing 400044,China)

机构地区：[1]中北大学机械工程学院,太原030051 [2]重庆大学机械工程学院,重庆400044

出　　处：《农业工程学报》2018年第23期59-66,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金(59975064)

摘　　要：为了准确提取齿轮箱中复合故障特征,该文选用变模态分解(variational mode decomposition,VMD)对振动信号进行处理,它能够将信号分解为多个固有模态函数(intrinsic mode function,IMF),但需预设分解层数k和惩罚因子;因此,为了能够自适应地确定分解层数k,该文提出了排列熵优化算法(permutation entroy optimization,PEO),该算法可以根据待分解信号的特点自适应的确定分解层数k;同时,为了解决VMD算法对噪声的敏感性,该文根据噪声辅助数据分析的思想,提出了改进VMD算法(modified variable modal decomposition,MVMD),该算法首先添加成对符号相反的高斯白噪声到原始信号,再利用VMD算法对其进行分解,经过多次循环,原始信号中的噪声相互抵消,而后将每次循环得到的每层IMF分别进行集成平均。利用该算法分别对含有多故障特征的齿轮箱仿真信号及实测信号进行处理,均提取出了故障特征。该文所提方法对封闭式功率流试验台进行复合故障提取,160和360 Hz的故障频率分别被提取出。该方法为齿轮箱复合故障诊断提供新思路。gearbox composite fault diagnosis has received extensive attention.The composite fault is that 2 or more faults occur simultaneously in the mechanical equipment.Due to the different degrees of damage of the composite fault,the complicated transmission path of the fault characteristic signal,and the interference of the background noise,the strength between the fault components is not balance.The weak fault features are usually overwhelmed by strong faults or noise and the strong faults are weakened by the high-frequency energy in the process of transmission,it is easy to be missed or misdiagnosis,especially in the case of variable speed and variable load,the coupling of composite fault features poses great challenge to the healthy and reasonable diagnosis of mechanical equipment.With the development of computer technology,some new novel adaptive noise reduction methods are proposed,including parametric decomposition methods and nonparametric decomposition methods,but they are more or less affected by noise interference and modal aliasing.Variational mode decomposition(VMD)decompose a complex signal into several different time scales,and each time scale contains a center frequency,which can overcome the modal aliasing phenomenon,variational mode decomposition is widely applied to gearbox composite fault diagnosis,and has achieved amazing results,but it needs to preset the decomposition layers k and penalty factor,and is sensitive to the background noise.In order to adaptively determine the number of decomposition layers k,this paper proposed permutation entropy optimization algorithm,which can adaptively determine the number of decomposition layers k according to the characteristics of the signal to be decomposed.In order to solve the sensitivity of VMD to noise,this paper proposed modified variational mode decomposition(MVMD)based on the idea of noise aided data analysis.The algorithm first added the opposite gauss white noise to the original signal,and then used VMD to decompose it.After repeated cycles,the noise

关 键 词：齿轮 算法 噪声 多故障 排列熵 变模态分解 

分 类 号：TN911.72[电子电信—通信与信息系统] TP206[电子电信—信息与通信工程]