基于优化SSA-VMD的滚动轴承故障信号降噪方法  

Noise reduction method of rolling bearing fault signal based on optimized SSA-VMD

作　　者：魏安凯 王娜[1,2] 丁军航 叶昱清 WEI Ankai;WANG Na;DING Junhang;YE Yuqing(School of Automation,Qingdao University,Qingdao 266071,China;Shandong Key Laboratory of Industrial Control Technology,Qingdao 266071,China;School of Rehabilitation Sciences and Engineering,University of Health and Rehabilitation Sciences,Qingdao 266071,China;Qingdao Hospital,University of Health and Rehabilitation Sciences(Qingdao Municipal Hospital),Qingdao 266071,China)

机构地区：[1]青岛大学自动化学院,山东青岛266071 [2]山东省工业控制技术重点实验室,山东青岛266071 [3]康复大学(筹)康复科学与工程学院,山东青岛266071 [4]康复大学青岛医院(青岛市市立医院),山东青岛266071

出　　处：《电子设计工程》2024年第16期64-68,共5页Electronic Design Engineering

摘　　要：针对滚动轴承故障信号降噪的问题,提出了一种基于优化麻雀搜索算法和变分模态分解的降噪方法。该方法利用优化麻雀搜索算法在既定范围内对变分模态分解的相关参数进行寻优,得到输入信号的最佳分解结果,根据时域相关系数选择有效的分量重构输入信号,从而实现对输入信号的降噪,通过滚动轴承的仿真故障信号和实际故障信号两方面分别验证该方法的有效性。结果表明,该方法相较于传统的变分模态分解方法拥有更好的降噪效果。A noise reduction method based on optimized Sparrow Search Algorithm and Variational Mode Decomposition is proposed to address the problem of denoising rolling bearing fault signals.This method uses the improved sparrow search algorithm to optimize the relevant parameters of the variational mode decomposition within the given range,obtain the optimal decomposition result of the input signal,and selects the effective component according to the time domain correlation coefficient to reconstruct the input signal and achieve noise reduction of the input signal.The effectiveness of this method was verified through simulation fault signals and actual fault signals of rolling bearings.The results show that the method has better noise reduction performance compared to traditional variational modal decomposition method.

关 键 词：信号降噪 轴承故障 变分模态分解(VMD) 麻雀搜索算法(SSA) 

分 类 号：TN911.7[电子电信—通信与信息系统]