摘要
以聚四氟乙烯(PTFE)为基体,改性纳米氧化镧(nano-La_(2)O_(3))、改性纳米蛇纹石(nano-serpentine)为添加剂,采用均匀设计法,制备nano-La_(2)O_(3)/nano-serpentine/PTFE复合材料。自制水环境模拟装置,设计并进行淡水环境复合材料摩擦学实验。使用Origin软件对实验数据进行曲线拟合,使用SPSS软件进行多元回归分析,得到摩擦学性能回归方程,通过MATLAB解出回归方程摩擦因数和磨损率理论最优解。以复合材料最优理论配比制作试件,进行摩擦学性能对比实验和磨损表面形貌分析。结果表明:复合材料摩擦学性能实验值与回归分析理论结果基本吻合,摩擦因数误差控制在5%以内,磨损率误差控制在10%以内,证明研究所用方法对复合材料摩擦学性能预测具有可行性。
The nano-La_(2)O_(3)/nano-serpentine/PTFE matrix composite was prepared by uniform design method and using PTFE as matrix,modified nano Lanthanum Oxide and modified nano serpentine as additives.The experiment of tribology of the composite in fresh water environment was designed and carried out with a self-prepared water environment simulator.Origin software was used for curve fitting of the experimental data,SPSS software was used for multiple regression analysis to obtain the linear regression equation of tribological performance,and the theoretical optimal solution of friction coefficient and wear rate of the regression equation was solved through MATLAB.The tribological properties of the composite with the optimal ratio were compared and the wear surface morphology was analyzed.The results show that the experimental values of tribological properties of the composite are basically consistent with the theoretical results of regression analysis,the friction coefficient error is controlled within 5%,and the wear rate error is controlled within 10%.This result proves this method has feasibility to the prediction of the tribological properties of the PTFE matrix composite.
作者
闫艳红
吴子健
卢欢
王腾彬
郝彩哲
贾志宁
YAN Yanhong;WU Zijian;LU Huan;WANG Tengbin;HAO Caizhe;JIA Zhining(College of Mechanical Engineering,Yanshan University,Hebei Innovation Center for Equipment Lightweight Design and Manufacturing,Qinhuangdao Hebei 066004,China;Department of mechanical Engineering,Chengde Petroleum College,Chengde Hebei 067000,China)
出处
《润滑与密封》
CAS
CSCD
北大核心
2021年第3期26-33,共8页
Lubrication Engineering
基金
河北省自然科学基金项目(E2016411005)。
关键词
PTFE基复合材料
淡水环境
均匀试验
多元回归
摩擦学性能预测
PTFE matrix composite
fresh water environment
uniform experiment
multiple regression
tribological performance prediction
