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作 者:花煜昌 刘力红[1] 杜鹏 HUA Yuchang;LIU Lihong;DU Peng(School of Mechancial Engineering,Anhui University of Science and Technology,Huainan Anhui 232001,China)
机构地区:[1]安徽理工大学机械工程学院,安徽淮南232001
出 处:《机床与液压》2022年第10期57-62,共6页Machine Tool & Hydraulics
基 金:安徽省高校自然科学基金重大项目(KJ2016SD18);国家自然科学基金项目(51804007)。
摘 要:采用前混合磨料水射流对Q235碳素结构钢进行切割实验,测量样品切口表面粗糙度;研究前混合磨料水射流的切割压力、喷嘴出口直径、切割靶距、切割速度和切割深度对样品切口表面粗糙度的影响规律;结合实验数据,建立表面粗糙度二次非线性回归预测方程。研究结果表明:前混合磨料水射流的切割压力、喷嘴出口直径与表面粗糙度呈负相关关系;切割靶距、切割速度、切割深度与表面粗糙度呈正相关关系;各因素的影响权重大小依次为:喷嘴出口直径、切割深度、切割压力、切割速度、切割靶距;影响表面粗糙度的实质因素为磨料流量和磨料能量;建立的表面粗糙度二次非线性回归预测方程的平均偏差为7.99%。The cutting experiment of Q235 carbon structural steel was carried out with the pre-mixed abrasive water jet,and the surface roughness of the sample cut was measured.The influence laws of the cutting pressure,nozzle outlet diameter,cutting target distance,cutting speed and cutting depth on the roughness of the sample cut surface were studied by the mixed abrasive water jet.Combined with experimental data,a second-order nonlinear regression prediction equation for surface roughness was established.The research results show that the cutting pressure of the pre-mixed abrasive water jet,the nozzle outlet diameter and the surface roughness are negatively correlated;the cutting target distance,cutting speed,cutting depth and surface roughness are positively correlated;the influence weight of each factor is in order:nozzle outlet diameter,cutting depth,cutting pressure,cutting speed,cutting target distance;the essential factors affecting surface roughness are abrasive flow and abrasive energy;the average deviation of the established surface roughness quadratic nonlinear regression prediction equation is 7.99%.
关 键 词:前混合磨料水射流 表面粗糙度 二次非线性回归预测方程
分 类 号:TH69[机械工程—机械制造及自动化]
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