磨料水射流切割混凝土的深度预测模型  

Depth predictions model of abrasive waterjet cutting concrete

作　　者：王宗龙[1] 胡寿根[1] 杨升[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：《机械研究与应用》2009年第1期25-27,共3页Mechanical Research & Application

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：在对磨料水射流切割混凝土分析基础上,应用BP人工神经网络理论,建立磨料水射流切割基于射流压力、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,为实际运用和进一步研究提供参考。Cutting depth model of abrasive water jet was established based on the experimental data of abrasive water jet cutring concrete by applying BP artificial neural network 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.

关 键 词：磨料水射流 人工神经网络 参数模型 

分 类 号：TP69[自动化与计算机技术—控制理论与控制工程]