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首页> 外文期刊>Applied Mathematical Modelling >The transformed inverse Gaussian process as an age- and state-dependent degradation model
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The transformed inverse Gaussian process as an age- and state-dependent degradation model

机译：高斯逆变换过程作为与年龄和状态相关的退化模型

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摘要

In this paper, a transformed inverse Gaussian (TIG) process is introduced as a new family of monotonic degradation models. Different from most state-of-the-art degradation models, which can only characterize age-dependent performance degradation, the TIG process model is mainly introduced for degradation modelling of industrial products with age-and state-dependent performance degradation. With this new model, promising properties include (1) the modelling capability for characterizing products observed at discrete time points with age- and state-dependent degradation, (2) the mathematical tractability for calculating the reliability function and remaining useful life distribution with high efficiency, and (3) the modelling flexibility of incorporating explanatory variables and random effects for investigating a product population with unit-to-unit heterogeneity. To facilitate the degradation modelling and analysis, methods for parameter estimation and model selection are developed under a coherent Bayesian framework. Simulation studies and real cases are presented to demonstrate the proposed degradation model and the Bayesian methods. (C) 2019 Elsevier Inc. All rights reserved.
机译：本文将变换高斯逆变换（TIG）过程作为一种新的单调退化模型引入。 TIG工艺模型不同于大多数仅能描述与老化有关的性能退化的最新技术，而TIG工艺模型主要用于对具有与老化和状态相关的性能退化的工业产品进行退化建模。有了这个新模型，有希望的特性包括（1）建模能力，用于表征在不连续的时间点观察到的具有年龄和状态相关的退化的产品；（2）数学易处理性，可以高效地计算可靠性函数和剩余使用寿命分布（3）结合解释变量和随机效应进行模型灵活性，以调查具有单位间异质性的产品群体。为了促进退化建模和分析，在一致的贝叶斯框架下开发了用于参数估计和模型选择的方法。仿真研究和实际案例被提出来证明所提出的退化模型和贝叶斯方法。 （C）2019 Elsevier Inc.保留所有权利。

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