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Reliability analysis for fatigue damage of railway welded bogies using Bayesian update based inspection

机译:基于贝叶斯更新的铁路转向架疲劳损伤可靠性分析。

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From the viewpoint of engineering applications, the prediction of the failure of bogies plays an important role in preventing the occurrence of fatigue. Fatigue is a complex phenomenon affected by many uncertainties (such as load, environment, geometrical and material properties, and so on). The key to predict fatigue damage accurately is how to quantify these uncertainties. A Bayesian model is used to account for the uncertainty of various sources when predicting fatigue damage of structural components. In spite of improvements in the design of fatigue-sensitive structures, periodic non-destructive inspections are required for components. With the help of modem nondestructive inspection techniques, the fatigue flaws can be detected for bogie structures, and fatigue reliability can be updated by using Bayesian theorem with inspection data. A practical fatigue analysis of welded bogies is utilized to testify the effectiveness of the proposed methods.
机译:从工程应用的角度出发,对转向架故障的预测在防止疲劳发生中起着重要作用。疲劳是一种复杂的现象,受许多不确定因素(例如载荷,环境,几何和材料特性等)的影响。准确预测疲劳损伤的关键是如何量化这些不确定性。在预测结构部件的疲劳损伤时,使用贝叶斯模型来考虑各种来源的不确定性。尽管对疲劳敏感结构的设计有所改进,但仍需要对组件进行定期无损检查。借助现代无损检测技术,可以检测转向架结构的疲劳缺陷,并通过使用带有检查数据的贝叶斯定理来更新疲劳可靠性。焊接转向架的实际疲劳分析被用来证明所提出方法的有效性。

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