摘要
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.
出处
《武汉理工大学学报（交通科学与工程版）》
2012年第5期1059-1063,共5页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
关键词
BAYES方法
随机加权法
信息融合方法
阈值
Bayes theory
random weighting method
information fusion technology
threshold
