基于小波包能量矩阵的轴承信号特征提取
Feature extraction of bearing vibration signal based on wavelet energy matrix
In order to recognize the operating conditions of bearings,a new approach for extracting features of vibration signals was proposed using the theory of wavelet transform and matrix eigenvalues. The method of energy was introduced and calculated using segmented datas , then a energy matrix was built and the matrix eigenvalues were got. Characte ristic parameters were defined based on the matrix eigenvalues.The relationship between the characteristic parameters and the operating condition of bearing were discussed.At last, a method of early age fault diagnosis that makes the wavelet coefficients multiply was brought up on the basis of Feature extraction. It is shown that the max characteristic parameters proposed can sensitively reflect the working performance of bearings.Therefore it could be considered as a parameter to inspect the condition of of bearings.The multiply of wavelet coefficients can be an efficient method of fault diagnose.
故障诊断 / 能量矩阵 / 小波包变换 / 矩阵特征值 / 特征参数 {{custom_keyword}} /
fault diagnose / energy matrix / wavelet transform / matrix eigenvalues / characteristic parameters {{custom_keyword}} /
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