磨料水射流切割深度的神经网络模型

在磨料水射流切割混凝土实验基础上,应用BP人工神经网络理论,建立了基于射流压力、靶距、磨料粒径、磨料流量、磨料喷嘴直径、磨料喷嘴长度及横移速度等射流参数的磨料水射流切割深度模型,通过模型预测结果与实验结果的比较,验证模型具有一定的精度,为实际的运用和进一步研究提供了参考。

Cutting Depth Model of Abrasive Waterjet Based on Neural Network Algorithm

Cutting depth model of abrasive water jet was established based on the experimental data of abrasive water jet cutting concrete by applying BP neural network algorithm and MATLAB neural network tool box,including the model parameters,waterjet pressure,standoff distance,diameter of abrasive,mass flow rate of abrasive,diameter of abrasive nozzle,length of abrasive nozzle and traversing velocity of jet.The result of comparison between the model predicted data and experimental data shows that the model is of reliable precision.The study could apply in practice and further studies in this field.