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首页> 外文期刊>Journal of the American Helicopter Society >Stochastic Updating Of Probabilistic Life Models For Rotorcraft Dynamic Components
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Stochastic Updating Of Probabilistic Life Models For Rotorcraft Dynamic Components

机译：旋翼飞机动态部件概率寿命模型的随机更新

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摘要

Probabilistic life models for rotary wing structures enable the development of maintenance programs that limit risk to acceptable levels. However, uncertainty in distributions of these models' parameters leads to overly conservative predictions of structural component lifetimes. Probabilistic modeling uncertainty can be reduced by updating distributions in the probabilistic model with information contained in maintenance data. The additional information permits more accurate statements on remaining life of structural components to be made, allowing condition-based maintenance and forecasting. A framework is developed to update probabilistic rotorcraft structural life models with maintenance data. The hierarchical Bayesian approach is adopted where the current parameter distributions serve as prior distributions, and maintenance data are included through a likelihood function. Updated distributions accounting for the inspection data are obtained using Bayes' rule. An example analysis of maintenance data is presented, where a probabilistic safe-life fatigue model is updated with crack detection and corrosion inspection findings.
机译：旋转机翼结构的概率寿命模型可以制定维护计划，以将风险限制在可接受的水平。但是，这些模型参数分布的不确定性导致对结构部件寿命的过于保守的预测。通过使用维护数据中包含的信息更新概率模型中的分布，可以减少概率建模的不确定性。附加信息可以更准确地说明结构部件的剩余寿命，从而可以进行基于状态的维护和预测。开发了使用维护数据更新概率旋翼飞机结构寿命模型的框架。采用分级贝叶斯方法，其中当前参数分布用作先验分布，并且通过似然函数包括维护数据。使用贝叶斯法则获得更新后的检验数据分布。给出了维护数据的示例分析，其中使用裂纹检测和腐蚀检查结果更新了概率安全寿命疲劳模型。

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