VMD方法在轴承故障定子电流信号诊断中的应用
2020-05-21时献江李万涛高庆康
时献江 李万涛 高庆康



摘 要:为了更好的判断滚动轴承的故障状态,利用定子电流的分析方法对轴承的主要故障机理和特征进行分析,针对轴承电流信号的特点,提出变分模态分解法(variational mode decomposition, VMD)来提取电流信号中一些微弱的故障信息,并简单给出如何对分解个数K进行取值的方法。在Matlab/Simulink下,建立一个仿真模型来模拟正常和故障状态下定子电流的变换情况,与搭建的模拟实验台所采集到的信号进行对比,并且利用变分模态分解法进行分析获得包络谱。通过理论仿真与实验环境下的对比分析,结果表明VMD方法能够从电流信号中分解出轴承的故障特征频率信息,是一种诊断滚动轴承故障的有效方法。
关键词:定子电流; 变分模态分解法; 轴承; 模拟实验; 仿真
DOI:10.15938/j.jhust.2020.01.004
中图分类号: TH16;TM315
文献标志码: A
文章编号: 1007-2683(2020)01-0022-07
Abstract:In order to judge the fault state of rolling bearing better, in this paper, the main fault mechanism and characteristics of the bearing are analyzed by using the stator current analysis method. According to the characteristic of the bearing signal, the VMD decomposition method is proposed to extract some weak fault information in current signals, and the method how to decompose the K numbers are given in the VMD decomposition methodUnder Matlab/Simulink, a simulation model is established to simulate the stator current transformation under normal and fault conditionsIt is compared with the signals collected by the simulation platform, and the variational modal decomposition method is used to obtain the envelope spectrumThrough the comparative analysis between the theoretical simulation and the experimental environment, it is shown that the VMD method can decompose the fault information of the bearing from the current signal, and it is an effective method to deal with the fault of the rolling bearing-
Keywords:stator current; variational mode decomposition; bearing; simulation experiment; simulation
0 引 言
轴承作为风电机组中重要的组成部分,恶劣的安装环境会对其造成严重的影响,甚至严重损坏系统的正常运行,更甚者危及人民的财产生命安全。因此,加大对轴承故障诊断的研究力度具有至关重要的意义[1]。
对轴承故障诊断的方法有很多,最常见的就是利用振动方法对轴承的故障进行诊断[2-3]。但是,利用振动的方法通过安装振动传感器所消耗的成本比较高,越来越多的人开始研究无传感器检测的方法。于是,Kryte[4]教授提出了定子电流分析法,一种无传感器的诊断故障的方法,只需要利用电流互感采集到定子电流信号就可以,定子电流法已经逐渐成为一种新的轴承故障诊断方法。……
