基于统计特征的滚动轴承性能退化分析研究

轴承作为旋转机械设备中的关键部件,其性能优劣影响着设备的运行质量。准确感知和预测轴承的性能退化趋势,对降低轴承的维护成本具有重要意义。轴承振动信号通常表现出非平稳特征,常规的时域和频域方法难以对轴承性能退化做出准确评估,为此提出了一种基于统计特征的性能退化分析方法。首先通过分布拟合获得滚动轴承合加速度信号的分布特征,然后构建退化指标描述轴承的性能衰退状态,最后设定失效阈值指标来检测轴承是否失效。结果表明,构建的退化指标可以直观有效地描述轴承的性能衰退状态,能够为轴承进一步的故障诊断与寿命预测奠定基础。

Analysis on performance degradation of rolling bearing based on statistical features

As the key part of the rotating machinery,its performance affects the operation guality of the equipment.Accurately perceiving and predicting the performance degradation trend of the bearing is of great significance for reducing its maintenance cost.Since the vibration signals of the bearing usually show non-stationary characteristics,it is difficult to accurately evaluate its performance degradationby conventional time-domain and frequency-domain method.Therefore,a performance degradation analysis method based on statistical characteristics was proposed.Firstly,the distribution fitting method was applied to obtain the distribution characteristics of the acceleration signals of the rolling bearing.Then,the degradation indexes were constructed to describe the performance degradation state of the bearing.Finally,the failure threshold index was set to judge whether the bearing was invalid or not.The results showed that the degradation indexescould describe the performance degradation state of the bearing intuitively and effectively,which laid foundation for further fault diagnosis and life prediction of the bearing.