全矢FSWT方法在轴承故障诊断中的应用  

Application of Full Vector Frequency Slice Wavelet Transform Method in Bearing Fault Diagnosis

作　　者：王坤[1] 李凌均[1] 郝旺身[1] 薛阳 WANG Kun;LI Ling-jun;HAO Wang-shen;XUE Yang(Machinery and Power Engineering College,Zhengzhou University,He’nan Zhengzhou 450001,China)

机构地区：[1]郑州大学机械与动力工程学院,河南郑州450001

出　　处：《机械设计与制造》2023年第12期205-208,共4页Machinery Design & Manufacture

基　　金：国家重点研发计划项目(2016YFF0203100)。

摘　　要：针对在滚动轴承故障诊断中,传统单通道原始信号存在输入信息缺失,经方法处理后导致诊断结论不一致的问题,将全矢谱分析技术和频率切片小波变换(Frequency Slice Wavelet Transform,FSWT)相结合,提出了全矢FSWT的方法进行故障检测与诊断。运用FSWT分析同源相互垂直的双通道原始样本,并选择合适的时频切片区间进行包络重构,接着对重构后的信号进行全矢融合,观察提取故障数据的特征频率以进行故障诊断。实验结果表明,该方法既能较好地提取故障特征信号,又能准确有效地诊断故障类型。In order to solve the problem of inconsistent diagnosis results from the lack of input information in the traditional single-channel original signal in the fault diagnosis of rolling bearings,the full-vector FSWT method is proposed by combining the full-vector spectrum analysis technology and frequency slice wavelet transform.FSWT was used to analyze the homologous and mutually perpendicular dual-channel original samples to select the appropriate time-frequency section interval for envelope reconstruction,complete vector fusion was performed for the reconstructed signals,and the characteristic frequency of fault data was extracted for fault diagnosis.Experimental results show that this method can not only extract fault characteristic signals well,but also diagnose fault types accurately and effectively.

关 键 词：频率切片小波 全矢谱 滚动轴承 故障诊断 

分 类 号：TH16[机械工程—机械制造及自动化]