摘要
以摩擦力矩电流信号时间序列表征滚动轴承服役期间性能运转状况,将时间序列分段处理并建立本征序列;基于灰关系,对轴承运转过程中每段摩擦力矩电信号进行排序,分别与本征序列相匹对进而获取灰置信水平;以灰置信水平的大小判定轴承运转的性能稳定性情况。然后将所分数据段自助再抽样,用最大熵法建立其概率密度函数,在所对应灰置信水平下获取估计区间;凭借计数过程,模拟出变异强度的原始信息;基于泊松过程建立可靠性函数,实时监测滚动轴承性能可靠性演变历程。仿真案例与试验研究表明:所提模型可真实监控轴承运转的性能稳定性及可靠性,有效解决具有不确定的强烈波动和趋势变化的时间序列问题。
The operation condition of roiling bearing performance is describled using time series of the friction torque current signal, which are segmented to establish intrinsic sequences. Based on grey relation, each section of the friction torque signal is sorted to match the intrinsic sequence, as a result, the grey confidence level is acquired. The grey confidence level is used to determine the extent of stability on bearing performance. Via bootstrap resampling for the segmented data, the probability density function is calculated by using the maximum entropy method, and estimated interval is obtained according to the corresponding grey confidence level. Relying on the counting process, the raw information of variation intensity is simulated. The rehahility function is constructed with the Poisson process to real-time monitor the reliability evolution of rolling bearing. Simulation cases and experimental test show that the proposed model can truly monitor the stability and reliability of bearing running performance, and effectively deal with the time series with strong fluctuation and varied trend.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2017年第6期1421-1431,共11页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(51475144)
河南省自然科学基金(162300410065)项目资助
关键词
滚动轴承
稳定性
可靠性
灰关系
泊松过程
rolling bearing
stability
reliability
grey relation
Poisson process
