小样本条件下一种旋转机械振动状态阈值的确定方法及应用

A Vibration Threshold-Setting′s Method of A Rotating Machinary and Its Appplication on Small Sample

针对旋转机械振动状态阈值设定时数据样本不足的情况,给出了一种基于Bayes-随机加权法的阈值确定方法.该方法综合运用了随机加权法、Bayes理论和验前信息融合技术,实现小样本条件下的振动特征值统计参数估计.通过与经典统计法和随机加权法的仿真对比研究,证明了其在小样本统计参数估计应用中的优越性.对离心泵机组故障模拟平台进行了整机振动状态阈值确定实验,能有效的实现设备振动状态评估.

The insufficient data sample causes the difficulty when setting the rotating machinary vibra- tion threshold. A threshold-setting ways based on the Bayes-random weighted method was presented, which is combining the random weighting method, Bayes theory and pre-test information fusion tech- nology for estimated the statistic parameters of the vibration eigenvalues on small sample. By compa- ring with the classical statistical method and the random weighted method, the simulating study indi- cated the advantage of applying the Bayes-random weighted method to estimating the statistic parame- ters on small sample. At the end of the paper, the vibration threshold-setting experiment on the cen- trifugal pump fault-simulating platform was done and the results showed that the Bayes-random weighted method can evaluate the vibration status of the rotating machinery effectively.