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Remaining Lifetime Prediction by Integrating Degradation Data with Lifetime Data

机译:通过将降级数据与生命周期数据集成在一起,剩余生命周期预测

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Aiming at the field degradation data of the target product and the lifetime data of the similar products, remaining lifetime (RL) prediction method is put forward. Wiener parameters are assumed to obey to union conjugate normal-inverse gamma distribution. Bayesian estimation model for Wiener parameters is built based on the target product field measured degradation data. Entire likelihood functions for degradation data and lifetime data are built. Prior estimation model for hyper parameter is built. By expectation maximization (EM) algorithm, the posterior hyper parameter estimates is obtained. The accuracy and applicability of the present method is verified by an example.
机译:针对目标产品的现场退化数据和同类产品的寿命数据,提出了剩余寿命(RL)预测方法。假设维纳参数服从联合共轭正反伽马分布。基于目标产品现场测得的降解数据,建立了维纳参数的贝叶斯估计模型。建立了退化数据和寿命数据的全部似然函数。建立了超参数的先验估计模型。通过期望最大化(EM)算法,获得后超参数估计。通过实例验证了本方法的准确性和适用性。

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