Abstract:Make a thorough inquiry for an approach to increase the signal dimension based on difference spectrum of singular value and a new fault diagnosis method for rolling bearings based on difference spectrum of singular value and stationary subspace analysis (SSA) is proposed. The first step is to obtain the singular value difference spectrum of the bearing original vibration signal, according to the peak distribution of singular value difference spectrum, different numbers of useful component signals are used to reconstruct new signal matrixes, so that the signal dimensions are increased .Then the multi-dimensional signals are used as inputs to SSA to obtain the stationary parts and non-stationary parts of the original signal. Finally, the selected non-stationary component which has the maximum kurtosis value is analyzed by the envelope spectrum to extract characteristic frequency of fault rolling bearing. The analysis of simulated signal and early fault signal of rolling bearing showed that the proposed method can accomplish the under-determined blind source separation of fault rolling bearings, which invalidate the effectiveness of the method.
唐贵基,庞彬,刘尚坤. 基于奇异差分谱和平稳子空间分析的滚动轴承故障诊断[J]. 振动与冲击, 2015, 34(11): 83-87.
Tang Gui-ji,Pang Bin,Liu Shang-kun. Fault diagnosis of rolling bearings based on difference spectrum of singular value and stationary subspace analysis. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(11): 83-87.
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