噪声与振动控制2016，Vol.36Issue(5)：139-143,5.DOI:10.3969/j.issn.1006-1335.2016.05.029
奇异值分解结合频率切片小波的齿轮故障特征提取
A Method of Fault Characteristic Extraction of Gears Based on Singular Value Decomposition and Frequency Slice Wavelet Transform
摘要
Abstract
Frequency slice wavelet transform is a powerful time-frequency analysis method. But its ability of fault characteristic identification is weak under the condition of strong noise background. Thus, a method of fault characteristic extraction combining the singular value decomposition with the frequency slice wavelet transform is proposed. First of all, the Hankel matrix is constructed using the original signal, the reconstruction order is determined based on the criterion of the unilateral maximum in the singular value difference spectrum, and the de-noising process is carried out. Secondly, the whole frequency domain analysis is performed for the de-noised signal using the frequency slice wavelet transform, and the distribution interval of the signal component is confirmed. Finally, the slice refinement analysis is performed for the signal with concentrated energy, and the fault characteristic of the gears can be extracted from the time-frequency spectrum of the reconstructed signal. Results of numerical simulation and signal measurement show that the proposed method can achieve accurate identification of the operation condition of the gears, and has some engineering significance.关键词
振动与波/齿轮/奇异值分解/频率切片小波变换/故障诊断Key words
vibration and wave/gear/singular value decomposition/frequency slice wavelet transform/fault diagnosis分类
机械制造引用本文复制引用
周福成,唐贵基,廖兴华..奇异值分解结合频率切片小波的齿轮故障特征提取[J].噪声与振动控制,2016,36(5):139-143,5.基金项目
河北省自然科学基金资助项目(E2014502052)；中央高校基本科研业务费专项资金 （E2014502052）
