故障预测算法稳定性实时评估方法

针对现有故障预测算法性能评估指标受实际剩余使用寿命约束的问题，从稳定性角度提出一种评估算法性能的方法。通过研究对象系统健康退化过程，在对象系统实际剩余使用寿命未知情况下，利用可以实时获得的剩余使用寿命预测值和已消耗寿命值，通过计算虚构寿命值的变异系数指标来客观评估故障预测算法的性能。为了验证所提方法的有效性，结合机电作动器故障演化模型仿真生成数据对递归最小二乘和粒子滤波两种故障预测算法的稳定性进行了实时评价。仿真结果表明，所提方法与运用已有指标、在获知剩余使用寿命理想值前提下得出的评估结果保持一致。

Real-time evaluation method for stability of fault prognostic algorithm

An evaluation method of fault prognostic algorithm from the perspective of stability was proposed for the existing evaluation metrics for fault prognostic algorithm were subjected to the actual remaining useful life. Based on studying upon the health degradation process of the system under test, according to the prognostic value of remaining useful life and the value of consumed life, the performance of fault prognostic algorithm could be assessed by calculating the coefficient of variance of the fictitious life before system failed. To verify the proposed method, the stability of recursive least squares algorithm and particle filtering algorithm was assessed with simulated data generated by the fault progression model of electro-mechanical actuator. Simulation results indicate that the proposed algorithm can arrive at the same evaluation conclusion as the existing methods which need the ideal value of remaining useful life of the system under test.