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Load Identification of the Gearbox Using Artificial Neural Networks

机译:使用人工神经网络负载齿轮箱的识别

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This paper proposes an approach to identify loads acting on the gearbox, which uses an artificial neural network to model the load-strain relationship in structural analysis. The identified results meet accuracy demands by comparing these outputs with experiment values .The paper demonstrates that artificial neural network can be used very effectively in load identification. The well-trained neural network reveals an extremely fast convergence and a high degree of accuracy in the gearbox load identification. Due to BP algorithm cannot work perfectly n the actual application, so many improved algorithm come up. In this study, an Improved Error Back Propagation algorithm is adopted to train artificial neural network.
机译:本文提出了一种识别作用在变速箱上的载荷的方法,它使用人工神经网络在结构分析中模拟负载应变关系。通过将这些输出与实验值进行比较,所识别的结果满足准确性要求。本文证明了人工神经网络可以在负载识别中非常有效地使用。训练有素的神经网络在齿轮箱负载识别中揭示了极快的收敛性和高度精度。由于BP算法无法完美地工作,所以许多改进的算法上升了。在该研究中,采用改进的误差反向传播算法来培养人工神经网络。

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