基于PSO算法的滑片-滑槽摩擦模型的参数识别分析

Research on Parameter Identification of Slider-chute Friction Model based on PSO algorithm

以滚动活塞压缩机滑片为研究对象,建立了滑片与滑槽的LuGre摩擦模型.将不同稳态速度下的摩擦力值利用自适应权重粒子群优化算法进行分析,对摩擦模型的静态参数进行识别,对不同预滑移阶段的摩擦力值进行分析,实现摩擦模型的动态参数识别,最终获得一种能够表征滚动活塞压缩机滑片周期性变化摩擦的LuGre摩擦模型,并对模型的准确性进行了验证,为分析滑片与滑槽的摩擦特性提供了依据.

By taking the sliding vanes of rolling piston compressor as the research object,the LuGre friction model between sliding vane and chute of rolling piston compressor was established.The static parameters of the friction model were identified by using adaptive weighted particle swarm optimization(AWPSO)algorithm to analyze the friction values at different steady-state velocities.Friction values at different pre-slip stages were analyzed to identify the dynamic parameters of the friction model.Finally,a LuGre friction model which can characterize the periodic variation of friction of sliding vanes of the rolling piston compressor was obtained,and the accuracy of the model was verified,which provides a basis for analyzing the friction characteristics of the sliding vanes and slideway.