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双螺杆挤出机异形内筒结构强度影响因素分析

Analysis of Factors Influencing the Structural Strength of Twin-screw Extruder Shaped Inner Cylinders
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摘要 异形内筒的厚度δi、相交圆中心距e、相交圆直径d是影响双螺杆挤出机强度的3个主要结构参数(简称3因素),一次局部薄膜应力PL、一次局部薄膜应力+二次应力P_(L)+P_(b)+Q是压力容器应力强度评定的2个主要应力类别。对3因素设定4个水平,进行3因素4水平正交试验,利用极差分析方法与方差分析方法处理正交试验数据。研究结果表明,因素δi、e、d对双螺杆异形内筒上危险截面处的应力P_(L)、P_(L)+P_(b)+Q均具有显著影响,对PL影响的主次排序为δi、e、d,对P_(L)+P_(b)+Q影响的主次排序为δi、d、e,对PL、P_(L)+P_(b)+Q影响的最佳方案均为δi(4)d(1)e(1)。采用多元回归分析拟合出了异形内筒结构危险截面应力PL及P_(L)+P_(b)+Q的多元回归方程,可用于双螺杆挤出机异形内筒结构应力的估算。 The thickness of the shaped inner cylinderδi,the center distance of intersecting circles e,and the diameter of intersecting circles d are the three main structural parameters(referred to as the three factors)that affect the strength of the twin-screw extruder.The primary local film stress P_(L),the primary local film stress+the secondary stress P_(L)+P_(b)+Q are the two main stress categories for the stress strength evaluation of pressure vessels.4 levels for 3 factors were set,3 factors and 4 levels orthogonal experiment were carried out,and use range analysis and variance analysis of the orthogonal test data were processed.The results show that the factorsδi,e and d have significant effects on the stress P_(L) andP_(L)+P_(b)+Q at the dangerous cross section on the shaped inner cylinder of twin-screw.The main order of the influence on PL isδi,e and d,and the main order of the influence on P_(L)+P_(b)+Q isδi,d and e.The optimal scheme for the influence of P_(L),P_(L)+P_(b)+Q isδi(4)d(1)e(1).The multiple regression equations of the dangerous section stress P_(L) and P_(L)+P_(b)+Q were fitted by multiple regression analysis,which could be used to estimate the stress of the special-shaped inner barrel of twin-screw extruders.
作者 柏凯旋 董金善 孙项羽 王涛 BAI Kai-xuan;DONG Jin-shan;SUN Xiang-yu;WANG Tao(School of Mechanical and Power Engineering,Nanjing Tech University,Nanjing 211816,China)
出处 《石油化工设备》 CAS 2024年第3期42-47,共6页 Petro-Chemical Equipment
关键词 双螺杆挤出机 异形内筒 结构强度 多元回归分析 twin-screw extruder shaped inner cylinder structural strength multiple regression analysis
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