基于BP人工神经网络的磨料水射流切割深度模型  

Cutting depth model of abrasive water jet based on artificial BP neural network

作　　者：杨升[1] 胡寿根[1] 王宗龙[1] 姚文龙[1] 

机构地区：[1]上海理工大学动力工程学院,上海200093

出　　处：《上海理工大学学报》2008年第6期528-530,共3页Journal of University of Shanghai For Science and Technology

基　　金：国家自然科学基金资助项目(50275097);上海市科学技术委员会资助项目(022912182)

摘　　要：在已知的磨料水射流切割混凝土实验数据的基础上,应用BP人工神经网络理论,并且借助MATLAB神经网络工具箱,建立磨料水射流切割深度模型.模型中包括的射流参数有射流压力、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.通过模型预测结果与实验结果的比较,表明模型具有一定的精度.Cutting depth model of abrasive water jet was established based on the experimental data of abrasive water jet cutting concrete by applying artificial BP neural network and MATLAB neural network tool box. The model includes several jet parameters： jet 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.

关 键 词：磨料水射流 人工神经网络 切割模型 

分 类 号：TP601[自动化与计算机技术—控制理论与控制工程] TP69[自动化与计算机技术—控制科学与工程]