Al_2O_(3f)+C_f/ZL109干摩擦磨损行为及其人工神经网络分析  

Dry Sliding Friction and Wear Behavior of Al 2O 3f +C f/ZL109 Composites and Its Analysis with Artificial Neural Networks

作　　者：于思荣[1] 刘耀辉[1] 于金江 康九洲 杜军[1] 

机构地区：[1]吉林工业大学材料科学与工程学院,吉林长春130025

出　　处：《摩擦学学报》1999年第3期198-203,共6页Tribology

基　　金：吉林省科学技术委员会资助

摘　　要：采用挤压铸造法制备了氧化铝及碳短纤维混杂增强 Ｚ Ｌ１０９ 合金复合材料，考察了该复合材料的干摩擦磨损行为．结果表明：该复合材料的摩擦磨损性能随纤维总体积分数的增加而降低；当纤维总体积分数一定时，随碳纤维含量的增加复合材料摩擦磨损性能降低．采用人工神经网络技术对该复合材料的干摩擦磨损试验结果进行了综合分析，其结果与试验值吻合较好．分析表明：纤维总体积分数较小时，碳纤维含量对复合材料耐磨性的影响较大，随纤维总体积分数的增大其影响减弱；无论纤维总体积分数如何变化，碳纤维含量对复合材料摩擦系数均有较大影响，这是其自润滑作用的结果；载荷较小时，该复合材料摩擦磨损的跑合时间较长；随载荷的增大摩擦系数减小；The dry sliding friction and wear behavior of Al 2O 3 and carbon short fiber hybrid reinforced ZL109 alloy composites fabricated by squeeze casting was investigated. The results show that the friction coefficient of the composites decreases while its wear resistance increases with theincrease of total fiber volume fraction ( φ ). When φ is fixed, the wear resistance of the composites increases with the increase of carbon fiber content ( φ c). The comprehensive analytical results of the friction and wear properties by artificial neural networks agree well with the experimental ones. When φ is small, φ c has considerable effect on the wear resistance, and the effect decreases with the increase of φ . An important effect of φ c on the friction coefficient is observed no matter how φ changes, which depends on the action of the self lubrication of carbon fiber. The running in time of the composites is long at a low load. The friction coefficient decreases with the increase of load. The effect of load on the friction coefficient becomes small during the steady stage of wear.

关 键 词：复合材料 人工神经网络 干摩擦磨损 汽车 

分 类 号：U465.6[一般工业技术—材料科学与工程]