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Study of the influence of the technological parameters on the weld quality using artificial neural networks

机译:利用人工神经网络研究工艺参数对焊接质量的影响

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This paper presents a study on the weld quality obtained by different values of the input parameters. The weld quality is characterized by two categories of parameters: geometrical parameters and mechanical parameters. They are dependent on the following process parameters: electric arc voltage, electric current intensity, welding speed, the feed wire velocity. Because the dependence between inputs and outputs is a nonlinear one was used an artificial feed forward neural network (ANN). The ANN was trained with the backpropagation algorithm, using as training patterns data measured from the mechanical process. This ANN can be used to estimate some parameters from future experiments of the mechanical process.
机译:本文对通过不同输入参数值获得的焊接质量进行了研究。焊接质量的特征在于两类参数:几何参数和机械参数。它们取决于以下过程参数:电弧电压,电流强度,焊接速度,送丝速度。由于输入和输出之间的依赖关系是非线性的,因此使用了人工前馈神经网络(ANN)。使用反向传播算法对ANN进行了训练,使用从机械过程中测得的数据作为训练模式。该人工神经网络可用于估算未来机械过程中的一些参数。

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