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An Additive Wiener Process-Based Prognostic Model for Hybrid Deteriorating Systems

机译：基于加纳维纳过程的混合劣化系统预测模型

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摘要

Hybrid deteriorating systems, which are made up of both linear and nonlinear degradation parts, are often encountered in engineering practice, such as gyroscopes which are frequently utilized in ships, aircraft, and weapon systems. However, little reported literature can be found addressing the degradation modeling for a system of this type. This paper proposes a general degradation modeling framework for hybrid deteriorating systems by employing an additive Wiener process model that consists of a linear degradation part and a nonlinear part. Furthermore, we derive the analytical solution of the remaining useful life distribution approximately for the presented model. For a specific system in service, the posterior estimates of the stochastic parameters in the model are updated recursively by using the condition monitoring observations based on a Bayesian framework with the consideration that the stochastic parameters in the linear and nonlinear deteriorating parts are correlated. Thereafter, the posterior distribution of stochastic parameters is used to update in real-time the distribution of the remaining useful life where the uncertainties in the estimated stochastic parameters are incorporated. Finally, a numerical example and a practical case study are provided to verify the effectiveness of the proposed method. Compared with two existing methods in literature, our proposed degradation modeling method increases the one-step prediction accuracy slightly in terms of mean squared error, but gains significant improvements in the estimated remaining useful life.
机译：由线性和非线性退化部分组成的混合劣化系统，在工程实践中经常会遇到，例如在船舶，飞机和武器系统中经常使用的陀螺仪。但是，很少有文献报道针对这种系统的降级建模。本文通过采用由线性退化部分和非线性部分组成的加性维纳过程模型，提出了一种混合退化系统的一般退化建模框架。此外，我们针对所提出的模型大致推导了剩余使用寿命的解析解。对于正在使用的特定系统，考虑到线性和非线性恶化零件中的随机参数是相关的，通过使用基于贝叶斯框架的状态监视观察，以递归方式更新模型中随机参数的后验估计。此后，随机参数的后验分布用于实时更新剩余使用寿命的分布，其中结合了估计的随机参数中的不确定性。最后，通过数值算例和实际案例研究验证了该方法的有效性。与文献中的两种现有方法相比，我们提出的降级建模方法在均方误差方面稍微提高了一步预测精度，但在估计的剩余使用寿命方面获得了显着改善。

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