滚动轴承故障振动信号中的冲击成分呈现显著的非高斯性，高阶累积量和高阶谱技术是处理非高斯信号的良好分析工具。在四阶累积量Teager峭度的基础上提出滑动Teager峭度的分析方法，并联合三阶谱1.5维谱，提出基于1.5维Teager峭度谱的滚动轴承故障诊断方法。该方法首先对轴承故障信号进行滑动Teager峭度计算，获得一个反应故障信号冲击特性的Teager峭度时间序列，然后通过计算Teager峭度时间序列的1.5维谱，提取出滚动轴承故障特征频率。通过仿真信号分析验证了该方法的解调性能和提取滚动轴承弱冲击故障特征的能力。最后分析了滚动轴承内圈故障实验测试信号，并和基于快速Kurtogram算法的共振解调方法进行对比分析，验证了该方法的有效性。
Abstract
The vibration signals of faulty rolling element bearings perform remarkable non-Gaussian characteristics, high order cumulants and high order spectra technology are good tools in analyzing non-Gaussian signals. A method named sliding Teager kurtosis was proposed on the basis of Teager kurtosis, and it was connected with 1.5-dimension spectrum to propose a new fault diagnosis method for rolling element bearings based on 1.5-dimensional Teager kurtosis spectrum. First, a time series of Teager kurtosis that could reflect the impulse characteristics of the vibration signal was obtained through computation of sliding Teager kurtosis, then fault characteristic frequency of rolling element bearing would be extracted by calculating 1.5-dimension spectrum of the Teager kurtosis time series. The analysis of simulated signals reflected the demodulation function and the ability of extracting weak impulse in rolling element bearing fault diagnosis. Finally, the effectiveness of the proposed method was validated by analyzing an experimental inner ring fault signal, compared with the method of resonance demodulation based on fast computation of kurtogram.
关键词
1.5维谱 /
滑动Teager峭度 /
滚动轴承 /
故障诊断
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Key words
1.5-dimension spectrum /
sliding Teager kurtosis /
rolling element bearing /
fault diagnosis
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