基于NGO-VMD和DBO-SVM的滚动轴承早期故障诊断  

Early Rolling Bearing Fault Diagnosis Based on NGO-VMD and DBO-SVM

作　　者：何凯 廖玉松[1] 张小光 HE Kai;LIAO Yusong;ZHANG Xiaoguang(School of Mechanical and Automotive Engineering,Chuzhou Vacationl and Technical College,Chuzhou 239000,China)

机构地区：[1]滁州职业技术学院机械与汽车工程学院,安徽滁州239000

出　　处：《西安航空学院学报》2024年第1期41-47,共7页Journal of Xi’an Aeronautical Institute

基　　金：安徽省高校自然科学研究重大项目(2023AH040389);滁州职业技术学院自然科学研究重点项目(YJZ-2020-06)。

摘　　要：针对滚动轴承早期故障阶段信号微弱难以提取和识别的问题,提出利用北方苍鹰算法优化变分模态分解参数,并结合蜣螂优化算法优化支持向量机的方法进行故障提取和分类识别。首先,采用北方苍鹰算法对变分模态的最佳参数进行搜索,将信号用变分模态分解为若干个本征模态函数;然后利用峭度选取最优本征模态函数;最后将其输入蜣螂优化算法-支持向量机诊断模型中进行故障分类识别。实验结果表明,北方苍鹰算法-变分模态分解方法在迭代次数和收敛精度上均有一定的优势,采用峭度选择最优本征模态函数,包络解调分析后提取早期微弱故障信号故障特征的能力最佳;蜣螂优化算法-支持向量机诊断模型能在故障信号微弱背景下,使故障诊断分类识别率有一定的提高。该方法具有较好的故障特征提取和分类识别能力,为滚动轴承早期故障诊断提供技术支持。In response to the weak signal in the early stage of bearing failure,which makes it difficult to extract and identify,NGO(northern goshawk optimization)is proposed to optimize VMD(variational mode decomposition)parameters,and the support vector machine method is combined with DBO(dung beetle optimizer)to optimize SVM(support vector machine)for fault extraction and classification recognition.Firstly,the NGO is used to search for the optimal parameters of the VMD,and the signal is decomposed into several intrinsic mode functions(IMF)using the VMD.Then,the kurtosis is used to select the optimal IMF.Finally,it is input into the DBO-VMD model for fault classification and recognition.The experimental results show that the NGO-VMD method has certain advantages in terms of iteration times and convergence accuracy.The kurtosis is used to select the optimal eigenmode function and the envelope demodulation analysis has the best ability to extract the fault features of early weak fault signals.Under the background of weak fault signal,the SVM diagnosis model can improve the classification and recognition rate of fault diagnosis to a certain extent.This method has good ability of fault feature extraction and classification recognition,and provides technical support for early fault diagnosis of rolling bearings.

关 键 词：滚动轴承 故障诊断 北方苍鹰算法 变分模态分解 蜣螂优化算法 支持向量机 

分 类 号：TH133.33[机械工程—机械制造及自动化]