考虑非线性退化与随机失效阈值的剩余寿命预测

针对广泛存在的非线性退化设备,现有方法尚未考虑随机失效阈值对剩余寿命预测结果的影响。因此,通过对设备性能退化过程进行分析,提出了一种综合考虑非线性退化与随机失效阈值的剩余寿命预测方法。基于Wiener过程构建了考虑个体差异与测量误差的非线性退化模型;基于卡尔曼滤波算法建立状态空间模型以实现对退化状态的在线更新;基于极大似然法估计失效阈值分布系数估计方法,得到随机失效阈值的概率分布;基于随机失效阈值推导出剩余寿命的概率分布,实现对剩余寿命的在线预测。算例研究表明,所提方法可以有效地提升剩余寿命预测的准确性,具备一定工程应用价值。

Remaining useful lifetime prediction based on nonlinear degradation processes with random failure threshold

For the nonlinear degradation equipment widely existed in practice, the current remaining useful lifetime (RUL) prediction methods do not consider the effect of random failure threshold. Therefore, by analyzing equipment''s degradation processes, the RUL prediction method based on nonlinear degradation processes with random failure threshold was proposed. A nonlinear degradation model based on Wiener process with the individual difference and measurement error was built in this work. Next, by applying the Kalman filtering algorithm and constructing the state-space model, the degradation states were updated synchronously. And then, the estimation method of failure threshold distribution parameters based on maximum likelihood estimation is proposed to obtain the probability distribution of the random failure threshold. Finally, an analytical and closed-form RUL distribution based on random failure threshold was derived, and the RUL prediction can be adaptively updated with the available observed data. The case study shows that the presented method can significantly improve the accuracy of RUL prediction and thus it has a certain engineering application value.