基于Alpha稳定分布的滚动轴承故障信号分析

Bearing Fault Signals Analysis Based on Alpha-Stable Distribution

提出了基于Alpha稳定分布的统计模型的滚动轴承故障信号分析方法,这种非高斯模型可以准确地描述具有脉冲特性的轴承故障信号。不同故障程度的轴承故障信号的特征指数α由Alpha稳定分布参数估计方法计算得到。实验结果表明,轴承故障信号属于Alpha稳定过程,各轴承故障信号的Alpha稳定密度分布在双对数坐标图中,适合经验概率密度分布以及它们的尾部都具有相同的重尾行为,表明这种统计模型对于不同故障程度的轴承信号都是有效的。

A new bearing fault signals analysis is proposed based on Alpha-stable distribution.Such a non-Gaussian model can describe the characteristics of bearing fault signals with impulsive behavior.The characteristic exponent for different fault degrees is estimated by a stable distribution parameter estimation method.Estimation result suggests that the bearing fault signals belongs to the Alpha-stable process.The Alpha-stable densities of every bearing fault signal fit well with the empirical probability density in log-log plots,and their tails possess the same heavy tail behavior.This validates the statistical model for different fault degree bearing signals.