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Damage prevention analysis of heavy-duty gear body based on finite element neural network

机译:基于有限元神经网络的重型齿轮机构损伤预防分析

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摘要

The method of damage prevention analysis of heavy-duty gear body based on finite element neural network is proposed to improve the effectiveness of damage prevention analysis of heavy-duty gear body. Firstly, a design platform for gearbox gears of caterpillar tractors is developed based on finite element theory, the three-dimensional model of the gear is designed on this platform, and the bending and contact finite element analysis of the gear teeth is carried out, the bending stress and contact stress of the gears are obtained, which provides a basis for the parameter design and reliability of the gears. Secondly, a neural network algorithm is introduced to predict and analyse the impact of damage data of heavy-duty gear body. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments.
机译:基于有限元神经网络的重型齿轮体损伤预防分析方法提高重型齿轮体损伤预防分析的有效性。 首先,基于有限元理论开发了履带拖拉机齿轮箱齿轮的设计平台,在该平台上设计了齿轮的三维模型,并进行了齿轮齿的弯曲和接触有限元分析。 获得齿轮的弯曲应力和接触应力,为齿轮的参数设计和可靠性提供了基础。 其次,引入了神经网络算法以预测和分析重型齿轮体损坏数据的影响。 最后,通过模拟实验验证了所提出的算法的有效性。

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