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A model for degradation prediction with change point based on Wiener process

机译：基于维纳过程的变点退化预测模型

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摘要

Prediction of degradation paths is important to condition-based maintenance (CBM). To address the detection of the existence of a sudden change point in a degradation path, a piecewise model based on Wiener process with a linear drift is proposed. Two different degradation drifts are introduced in the model as hidden states. Based on the Bayesian theorem, the likelihood function is given and the algorithm of parameter estimation is presented subsequently. Meanwhile, the Kalman filter and the smoother algorithm are used to estimate the hidden states. And we detect the change point of the two-stage degradation according to the concordance correlation coefficient. To validate the proposed method, a numerical simulation and a case study of bearing are presented at last.
机译：退化路径的预测对于基于状态的维护（CBM）很重要。为了解决退化路径中突变点存在的检测问题，提出了一种基于维纳过程的线性漂移分段模型。在模型中引入了两种不同的降级漂移作为隐藏状态。基于贝叶斯定理，给出了似然函数，并提出了参数估计算法。同时，使用卡尔曼滤波器和平滑算法来估计隐藏状态。并根据一致性相关系数检测出两阶段退化的变化点。为了验证该方法的有效性，最后对轴承进行了数值模拟和实例研究。

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