Neural networks with NARX structure for material lifetime assessment application

M. I. P. Hidayat, P. S. Yusoff, W. Berata
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引用次数: 6

Abstract

In the present paper, neural networks (NN) with non-linear auto-regressive exogenous inputs (NARX) structure is developed and further applied for material lifetime assessment application. Rational of the use of the NARX structure in the application was emphasized and linked to the concept of constant life diagram (CLD), the well known concept in fatigue of material analysis and design. Fatigue life assessment was then performed and realized as one-step ahead prediction with respect to each stress level corresponding to stress ratio values arranged in such a way that transition took place from a fatigue region to another one in the CLD. As a result, material lifetime assessment can be fashioned for a wide spectrum of loading in an efficient manner. The simulation results for different materials and loading situations are presented and discussed.
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基于NARX结构的神经网络在材料寿命评估中的应用
本文发展了具有非线性自回归外源输入(NARX)结构的神经网络,并将其进一步应用于材料寿命评估。强调了在应用中使用NARX结构的合理性,并将其与材料疲劳分析和设计中众所周知的概念——恒寿命图(CLD)的概念联系起来。然后进行疲劳寿命评估,并实现对应力比值对应的每个应力水平的一步提前预测,以便在CLD中从一个疲劳区域过渡到另一个疲劳区域。因此,材料寿命评估可以塑造为一个有效的方式,广泛的负载谱。给出并讨论了不同材料和载荷情况下的模拟结果。
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