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Rubber fatigue life prediction using a random forest method and nonlinear cumulative fatigue damage model

机译:橡胶疲劳寿命预测使用随机森林方法和非线性累积疲劳损伤模型

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摘要

In this study, a random forest machine-learning method is introduced on the basis of the analysis of measured constant amplitude stress fatigue data. This method aims to predict rubber fatigue life under constant amplitude stress. Strain mean value, strain amplitude, and strain ratio are used as independent variables, and the prediction model of rubber fatigue life under constant amplitude stress is established. A nonlinear cumulative fatigue damage model is proposed to calculate rubber fatigue life under the variable amplitude stress. Results show that the random forest method has high precision and generalization capability for rubber fatigue life prediction under constant amplitude stress and the nonlinear cumulative fatigue damage model could be employed to calculate the fatigue life of rubber under variable amplitude stress with enough accuracy according to the constant amplitude stress fatigue life data. This research can provide a reference for rubber fatigue life prediction. (c) 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 48519.
机译:在该研究中,基于测量的恒定幅度应力疲劳数据的分析来引入随机林机学习方法。该方法旨在在恒定幅度应力下预测橡胶疲劳寿命。应变平均值,应变幅度和应变比用作独立变量,建立了恒定幅度应力下橡胶疲劳寿命的预测模型。建议在可变幅度应力下计算橡胶疲劳寿命的非线性累积疲劳损伤模型。结果表明,随机森林方法具有高精度和普遍幅度应力的耐橡胶疲劳寿命预测的概括能力,并且可以采用非线性累积疲劳损伤模型来根据恒定的可变幅度应力计算橡胶的疲劳寿命幅度应力疲劳寿命数据。该研究可以为橡胶疲劳寿命预测提供参考。 (c)2019 Wiley期刊,Inc.J.Phill。聚合物。 SCI。 2019,136,48519。

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