摘要
为了充分挖掘转子振动信号的特征信息,研究提出了一种基于FFT和EWT的转子振动信号特征提取方法。从转子实验台获取转子四种状态的振动信号,将转子特征频率和EWT模态分量组合构成多维特征向量,利用K均值聚类法对比不同方案识别转子状态的正确率,选出最优的特征向量方案,达到了较高的状态识别正确率。
In order to get the full features of the rotor vibration signal,a feature extraction method is proposed based on the fast Fourier transformation( FFT) and the empirical wavelet transform( EWT). The vibration signals of four states of the rotor are obtained from the rotor tests. Multi-dimensional eigenvectors are then composed with the rotor characteristic frequencies and the EWT modal components. The K-means clustering method is used to compare the accuracy of different schemes for identifying the rotor state,and the optimal eigenvector scheme is selected. The results show that high accuracy is achieved in the state recognition with the proposed method.
引文
[1]杨永锋,吴亚锋.经验模态分解在振动分析中的应用[M].北京:国防工业出版社,2013
[2]Huang N E,Shen Z,Long S R,et al. The empirical mode decomposition and the hilbert spectrum for nonlinear and nonstationary time series analysis[J]. Proceedings of the Royal Society of Landon A:Mathematical,Physical&Engineering Sciences,1998,454(1971):903-995
[3]Gilles J. Empirical wavelet transform[J]. IEEE Transactions on Signal Processing,2013,61(16):3999-4010
[4]陈学军,杨永明.采用经验小波变换的风力发电机振动信号消噪[J].浙江大学学报:工学版,2018,52(5):988-995
[5]李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究[J].仪器仪表学报,2014,35(11):2423-2432
[6]赵妙颖,许刚.基于经验小波变换的变压器振动信号特征提取[J].电力系统自动化,2017,41(20):63-69,91
[7]卢娜.基于多小波的水电机组振动特征提取及故障诊断方法研究[D].武汉:武汉大学,2014
[8]安周鹏,肖志怀,孙召辉,等.改进小波阈值降噪算法在水电机组信号处理中的应用[J].中国农村水利水电,2014(12):165-168,172
[9]Liu D,Zeng H,Xiao Z,et al. Fault diagnosis of rotor using EMD thresholding-based de-noising combined with probabilistic neural network[J]. Journal of Vibroengineering,2017,19(8):5920-5931
[10]向玲,李媛媛.经验小波变换在旋转机械故障诊断中的应用[J].动力工程学报,2015,35(12):975-981
