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首页> 外文期刊>Expert Systems with Application >Application of adaptive neuro-fuzzy inference system in modeling fatigue life under interspersed mixed-mode (I and II) spike overload
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Application of adaptive neuro-fuzzy inference system in modeling fatigue life under interspersed mixed-mode (I and II) spike overload

机译:自适应神经模糊推理系统在散布混合模式(I和II)尖峰过载下的疲劳寿命建模中的应用

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摘要

In service components and structures frequently come across complicated fatigue loading situations such as interspersed mixed-mode (I and II) spike load on subsequent mode-1 fatigue crack growth. The design ers rely on different fatigue life prediction methodology in order to avoid costly and time consuming fati gue tests. Earlier authors' have proposed exponential and ANN models to predict the fatigue life of 7020 T7 and 2024 T3 Al alloys under the above loading conditions. In the present work, an attempt has been made to predict the fatigue life by adopting adoptive neuro-fuzzy inference (ANFIS) technique. It is observed that the predicted results for both the alloys are within the maximum range of 0.05% in com parison to experimental findings.
机译:在使用中,组件和结构经常遇到复杂的疲劳载荷情况,例如在随后的1型疲劳裂纹扩展上散布的混合模式(I和II)峰值载荷。设计人员依靠不同的疲劳寿命预测方法来避免昂贵且费时的疲劳测试。早期的作者提出了指数和ANN模型来预测在上述载荷条件下7020 T7和2024 T3铝合金的疲劳寿命。在当前的工作中,已经尝试通过采用过继神经模糊推理(ANFIS)技术来预测疲劳寿命。可以观察到,与实验结果相比,两种合金的预测结果均在0.05%的最大范围内。

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