摘要
为挖掘滚动轴承性能退化的更深层信息,建立了性能退化率与时间序列相似度之间的灰关系评估模型。首先,基于最大熵泊松计数原理计算性能退化率;然后,选取最佳性能时期的振动数据序列作为本征序列,分别计算其他振动数据序列与本征序列的相似性(基数贴近度);最后,基于灰关系分析法求解灰置信水平,分析性能退化率与时间序列间相似性的关联程度。仿真及实际案例表明,性能退化率与时间序列间相似性的灰置信水平分别为85.275%和90.5%,两者之间的关联程度非常高。将2个指标结合使用可以更全面地获取滚动轴承性能退化的深层次信息。
The grey relation evaluation model is established between performance degradation rate and time series similarity to excavate more deep information about performance degradation of rolling bearings.Firstly,the performance degradation rate is calculated based on maximum entropy Poisson counting principle.Then,the vibration data sequence in the period of optimum performance is selected as intrinsic sequence,and the similarities(cardinal closeness)are calculated between other data sequences and intrinsic sequence respectively.Finally,the grey confidence level is calculated based on grey relation analysis method,so as to analyze correlation degree between performance degradation rate and time series similarity.The simulation and actual cases show that the grey confidence levels are 85.275%and 90.5%between performance degradation rate and time series similarity,and the relevance between them is very high.The deep information about performance degradation of rolling bearings is obtained more comprehensively by using two indexes together.
作者
米月花
MI Yuehua(School of Information and Mechatronics Engineering,Zhengzhou Business University,Gongyi 451200,China)
出处
《轴承》
北大核心
2020年第7期30-35,共6页
Bearing
基金
教育部产学研协同育人项目(201802108033)。
关键词
滚动轴承
性能
退化
时间序列
相似性
灰关系分析
rolling bearing
performance
degradation
time series
similarity
grey relation analysis
