基于析因试验的连杆衬套磨损分析

柴油机连杆衬套-活塞销摩擦副的耐磨性能直接影响柴油机的使用寿命。基于完全析因试验,以主轴转速、配合间隙、加载载荷作为试验因素,磨损量作为评价指标,获得试验因素主效应及交互效应的主次顺序。结果表明:试验因素之间的交互效应是存在的,且超过某些单个因素的主效应。另外在单个因素中,主轴转速的主效应最强。利用RBF神经网络对高转速下的连杆衬套磨损量进行的预测,将预测值与实测值进行对比,发现网络具有较强的预报性能,可以有效提高参数的设计效率及降低实际实验所需的成本。

Analysis on the Wear Loss of Connecting Rod Bushing Based on Factorial Experiment

The wear resistance of the connecting rod bushing of the diesel engine has a direct influence on the service life of the diesel engine. With the spindle speed, the coordination gap and the load as the experimental factors, and wear loss as evaluation index, the main effects and interaction effects of the experimental factors were obtained based on the full factorial experiment. The results show that the interaction effect between experimental factors is existed, and this interaction effect surpass the main effect of a certain factor to some degree. In addition, the main effect of the spindle speed is the strongest in the single factor. Using RBF neural network to predict the wear loss of connecting rod bushing in highSrotationalSspeed and compared with the measured value, it is found that RBF neural network has strong prediction performance. It can effectively improve the design efficiency of parametersSand reduce the cost of actual experiment.