基于奇异值熵提取与北方苍鹰算法优化SVM方法轴承故障诊断研究  

Optimization of SVM bearing fault diagnosis based on singular value entropy extraction and northern goshawk algorithm

作　　者：李易璇 杨平[1] Li Yixuan;Yang Ping(School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,China)

机构地区：[1]沈阳工业大学信息科学与工程学院,沈阳110870

出　　处：《国外电子测量技术》2024年第12期211-223,共13页Foreign Electronic Measurement Technology

摘　　要：现有轴承故障诊断的研究成果在运用于实际生产生活中时,存在故障数据样本复杂以及传统智能优化算法调整参数众多等情况。针对直接采用轴承故障数据建立诊断模型时准确率较低且调整参数复杂的问题,提出一种基于奇异值熵与北方苍鹰算法结合卷积神经网络优化支持向量机的滚动轴承故障诊断方法。首先选取轴承故障的振动信号与声发射信号作为数据集,进行不同方式的模态分解;然后通过峭度值、欧氏距离、均方差,选择有效本征模态函数分量重组信号,提取奇异值熵为特征值;最后使用北方苍鹰算法结合卷积神经网络优化支持向量机的算法模型进行故障诊断。实验结果表明,所提方法不仅有效提取故障特征,并且在轴承故障的振动信号数据集分类中准确率达到97%以上,在声发射信号数据集中分类准确率达到了99%。When the existing research results of bearing fault diagnosis are applied to actual production and life,there are complicated fault data samples and numerous parameters adjusted by traditional intelligent optimization algorithms.Aiming at the problems of low accuracy and complicated parameter adjustment when using bearing fault data directly to establish diagnosis model,a rolling bearing fault diagnosis method based on singular value entropy and Northern Goshawk algorithm combined with convolutional neural network optimization support vector machine was proposed.Firstly,the vibration signal and acoustic emission signal of bearing fault are selected as data set,and the mode decomposition is carried out in different ways.Then,by using kurtosis value,Euclidean distance and mean square deviation,the effective eigenmode function component recombination signal is selected,and the singular value entropy is extracted as the eigenvalue.Finally,the Northern Goshawk algorithm combined with convolutional neural network is used to optimize the algorithm model of support vector machine for fault diagnosis.The experimental results show that the proposed method can not only extract fault features effectively,but also has a classification accuracy of more than 97%in vibration signal data set and 99%in acoustic emission signal data set.

关 键 词：轴承故障诊断 奇异值熵 北方苍鹰算法 卷积神经网络 支持向量机 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程] TN06[自动化与计算机技术—控制科学与工程]