摘要
针对风机齿轮箱振动信号噪声对系统故障诊断产生干扰的问题,研究了对信号进行降噪处理的方法,提出了一种基于变分模态分析的方法。对数据进行了预处理,通过维纳滤波去除了采集信号中的噪声成分,利用了变分模态分解迭代寻找模型最优解,确定了各分量频率中心和带宽,实现了不同频率成分有效分离;采用了完全非递归分解模型,有效避免了经验模态分解中的模态混叠现象,并且利用局部均值分解自适应的特点,对其分解结果进行了频谱分析,将其作为变分模态分解的模态个数K选取的依据,使得K值最优;通过MATLAB平台仿真对所提方法进行了仿真验证。研究结果表明:所提方法在避免模态混叠的同时,达到了很好的降噪效果并且具有很强的鲁棒性,可以大大减弱风机组故障诊断过程中振动信号噪声的干扰。
Aiming at the problem that the vibration signal noise of the fan gear box interfered with the system fault diagnosis,the method of signal noise reduction was studied.A method based on variational modal analysis was proposed to preprocess the data,and the collected signal was removed by Wiener filtering.Variational mode decomposition iteration was used to find the optimal solution of the model,the frequency center and bandwidth of each component was determined,and the effective separation of different frequency components was realized.A completely non-recursive decomposition model was used to avoid modal aliasing in empirical mode decomposition effectively.The characteristics of local mean decomposition were used to perform spectral analysis on the decomposition results,which was used as the basis for the selection of the number of modes K,so that the K value was optimal.The method was verified by simulation.The results show that the prop method achieves good noise reduction effect while avoiding modal aliasing and has strong robustness,which can greatly reduce the interference of vibration signal noise.
作者
许志华
潘庭龙
XU Zhi-hua;PAN Ting-long(Electrical Engineering College,Yancheng Institute of Technology,Yancheng 224051,China;IoT Engineering College,Jiangnan University,Wuxi 214000,China)
出处
《机电工程》
CAS
北大核心
2021年第1期129-132,共4页
Journal of Mechanical & Electrical Engineering
基金
国家自然科学基金资助项目(61672266)。
关键词
变分模态分解
经验模态分解
局部均值分解
齿轮箱振动
降噪
variational mode decomposition(VMD)
empirical mode decomposition(EMD)
local mean decomposition(LMD)
gearbox vibration
noise reduction
作者简介
许志华(1979-),男,江苏盐城人,硕士,讲师,主要从事电子技术设计与应用、信号分析与处理方面的研究。E-mail:58038372@qq.com;通信联系人:潘庭龙,男,博士,教授。E-mail:tlpan@jiangnan.edu.cn。
