摘要
通过研究产品故障发生的机理,建立了基于Gamma退化过程的状态空间模型,运用EM-PF参数估计方法对模型中的参数进行求解,确定模型的具体形式,进而得出产品剩余寿命的分布函数和概率密度函数。该剩余寿命预测方法将退化状态与故障阈值联系起来,从而降低了剩余寿命预测的误差,以轴承磨损量特征进行建模,完善了状态信息与剩余寿命之间的相互关系。利用剩余寿命的概率密度函数建立了以费用最小为目标的维修决策模型,确定最优的维修更换时间并实现维修决策的优化。最后用轴承寿命试验所得到的数据对模型进行了验证,实例结果证明该模型是可行有效的。
By studying the failure mechanism of the product, the state space model is established based on Gamma de- terioration process. The model parameters are solved with the EM - PF parameter estimation method, and the concrete form of model is confirmed. The distribution function and probability density function of remaining life are obtained. The prediction method combines the deterioration state with failure threshold, which reduces the error. The wear char- acteristics of bearings are modeled; the correlations between state information and remaining life are completed. Ac- cording to the probability density function of remaining life, a maintenance decision - making model is founded up, whose target is to get the most proper replacement time, optimizing the maintenance decision - making. At last, the da- ta of the bearing life experiment is taken for an example to verify the model, and the result shows that the model is prac- tical and effective.
出处
《轴承》
北大核心
2013年第4期44-49,共6页
Bearing
基金
"十二五"武器装备预先研究项目(51327020101)
关键词
滚动轴承
Gamma退化过程
剩余寿命
维修决策
rolling bearing
Gamma deterioration process
residual life
maintenance decision -making
