Abstract

The relationship between the parameters of the load-displacement curves and shear fracture area (SFA) of samples during impact bending tests has been studied. Using neural networks, a correspondence has been established between the form of the load-displacement curve and the fracture structure in a series of different microstructures. The applicability of the trained neural network to low-alloy steel with a microstructure that is different from the microstructures of the samples used in training has been tested. The minimal set of parameters of the load-displacement curve describing the shear fracture area of the sample is established. The nonlinearity of the relationship between the parameters of the dynamic curve and the shear fracture area of the sample is shown.

中文翻译：

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用神经网络分析低合金钢的载荷-位移曲线与断裂特性的关系

摘要

研究了冲击弯曲试验过程中载荷-位移曲线的参数与试样的剪切断裂面积（SFA）之间的关系。使用神经网络，已经在一系列不同的微结构中建立了载荷－位移曲线的形式与断裂结构之间的对应关系。测试了训练后的神经网络对显微组织与训练所用样品的显微组织不同的低合金钢的适用性。建立描述样品剪切断裂面积的载荷-位移曲线的最小参数集。示出了动态曲线的参数与样品的剪切断裂面积之间的关系的非线性。