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A Novel Process Model of Ship Rust Removal by Premixed Abrasive Jet based on Neural Network

机译:基于神经网络的预混磨料喷射除锈工艺模型

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In view of the technological requirements of the development of green shipbuilding technology on the effect of ship surface rust removal, the premixed abrasive jet technology is used to remove rust. Because the rust removal of ships with premixed abrasive jet is influenced by multiple parameters and has a high nonlinear relationship between various parameters, the accurate process model of it is difficult to establish. On the basis of artificial neural network modelling technology, the model of ship rust removal with premixed abrasive jet is built. The model takes the system pressure, the target distance, the moving speed of the spray gun and the particle size of the abrasive as input parameters, and the score which can most reflect the effect of the rust removal as output parameter. The test results show that the prediction error of the model is small, and it can better reflect the process rule between the effect of the premixed abrasive jet and the process parameters. We can guide the selection of process parameters according to the model.
机译:鉴于绿色造船技术的发展对船舶表面除锈效果的技术要求,采用预混合磨料喷射技术除锈。由于带有预混合磨料射流的船舶除锈受多个参数的影响,并且各个参数之间具有高度的非线性关系,因此难以建立精确的工艺模型。在人工神经网络建模技术的基础上,建立了预混磨料喷射除锈模型。该模型将系统压力,目标距离,喷枪的移动速度和磨料的粒径作为输入参数,并且最能反映除锈效果的分数作为输出参数。试验结果表明,该模型的预测误差小,能较好地反映出预混磨料射流效果与工艺参数之间的工艺规律。我们可以根据模型指导过程参数的选择。

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