陈 剑,阚 东,孙太华,张 磊.基于 SVD-VMD 和 SVM 滚动轴承故障诊断方法[J].电子测量与仪器学报,2022,36(1):220-226 |
基于 SVD-VMD 和 SVM 滚动轴承故障诊断方法 |
Rolling bearing fault diagnosis method based on SVD-VMD and SVM |
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DOI: |
中文关键词: 故障诊断 奇异值峰度差分谱 变分模态分解 故障特征提取 信号降噪 |
英文关键词:fault diagnosis singular value kurtosis difference spectrum variational mode decomposition fault feature extraction signal
noise reduction |
基金项目:国家自然科学基金青年基金(11604070)、安徽省科技重大专项(17030901049)项目资助 |
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中文摘要: |
针对故障滚动轴承振动信号中含有干扰信号,难以准确提取出故障信息,提出了一种基于奇异值分解(SVD)、变分模态
分解(VMD)、和支持向量机(SVM)的滚动轴承故障诊断方法。 首先利用奇异值分解对信号进行处理,根据奇异值峰度差分谱
来确定分解后重构矩阵的有效阶数,然后根据该有效阶数重构信号,对重构后的信号进行 VMD 分解,根据上述有效阶数确定分
解的本征模态函数(IMF)分量的个数,从分解后的 IMF 分量中提取故障特征参数,将其作为支持向量机的输入参数进行故障诊
断。 最后采用合肥工业大学轴承试验机进行验证,并与直接进 VMD 分解及基于带通滤波器信号去噪的故障诊断方法进行对
比,结果表明该方法能有效识别滚动轴承的故障类型,可用于滚动轴承故障诊断。 |
英文摘要: |
Vibration signals of fault rolling bearings contain interference signals, which makes it difficult to extract fault information
accurately. In this paper, a fault diagnosis method for fault rolling bearings was proposed based on singular value decomposition (SVD),
variational mode decomposition ( VMD) and support vector machine ( SVM). First, the singular value decomposition was used to
process the signal, and the effective order of the reconstructed matrix was determined according to the kurtosis difference spectrum of the
singular value. Then, the reconstructed signal was reconstructed according to the effective order, and the VMD decomposition was
performed on the reconstructed signal. The number of the decomposed intrinsic mode function ( IMF) components was determined
according to the above effective order. From the IMF component of the decomposed to extract the fault characteristic parameters, as the
input parameters of support vector machine ( SVM) to fault diagnosis. Finally validated bearing tester adopts Hefei university of
technology, and directly into the decomposition of VMD and band-pass filter signal denoising based fault diagnosis method is compared,
the results show that the method can effectively identify roller bearing fault type and can also be used for rolling bearing fault diagnosis. |
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