GH99合金TIG焊接接头拉伸性能的人工神经网络预测

Prediction of tensile property of TIG welding joints in GH99 alloy by artificial neural network

摘要: 利用Matlab7.0软件建立了用于预测GH99高温合金焊接接头拉伸性能的改进算法的多层BP神经网络.以焊接电流、焊接速度、脉冲频率、重熔次数、板厚、装配间隙、坡口与连接形式作为输入参数,抗拉强度、屈服强度和断后伸长率分别作为输出值.结果表明,改进算法的多层BP神经网络能够很好的预测GH99高温合金TIG焊接接头的拉伸性能,抗拉强度、屈服强度与断后伸长率预报值与试验值的平均相对误差分别为 -0.76%,1.71%和2.30%.

Abstract: Multilayer BP network model based on improved algorithm was established with Matlab 7.0 software to predict the tensile property of TIG welding joints of GH99 superalloy. The input parameters of the model consisted welding current, welding speed, pulse frequency, remelting times, plate thickness, assembly clearance and weld groove. The outputs of the Artificial Neural Network(ANN) model included property parameters, such as tensile strength, yield strength and elongation. The calculated results showed that the multilayer BP network model based on improved algorithm could predict the tensile property of TIG welding joints of GH99 superalloy. The calculated values were in good agreement with measured data, and the average relative errors between calculated values and measured data of tensile strength, yield strength and elongation were -0.76%, 1.71% and 2.30% respectively.