磁流变阻尼器的性能试验与神经网络建模  

Test of a MR damper and its modeling using neural network

作　　者：王修勇[1] 宋璨[1] 陈政清[1] 孙洪鑫[1] 陈丕华[1] 

机构地区：[1]湖南大学土木工程学院,长沙410082

出　　处：《振动与冲击》2009年第4期42-46,共5页Journal of Vibration and Shock

摘　　要：磁流变阻尼器是一种新型的智能振动控制装置。通过磁流变阻尼器的性能试验,研究了在不同电流输入下阻尼力-位移、阻尼力-速度之间的关系,分析了摩擦型磁流变阻尼器的主要特点。采用BP神经网络,建立了磁流变阻尼器的正向模型和逆向模型。仿真结果显示,神经网络模型能准确地预测磁流变阻尼器的阻尼力和控制电流,证明该方法的有效性。与已有的模型相比,具有精度高,计算简便等特点。A magnetorheological (MR) damper is a new kind of smart device for vibration control. Through characteristic testing of a MR damper, its force-displacement and force-velocity relationship under different currents were studied; the main features of a friction-type MR damper were analyzed. A forward model and an inverse model of a MR damper were established by using BP neural network. Simulation results showed that the neural network model could accurately predict damping force and current of the MR damper, so the proposed approach was effective. Comparing with the existing model, the features of the model built here were more accurate and easier to compute.

关 键 词：摩擦型磁流变阻尼器 性能试验 滞回环 BP神经网络 正向模型 逆向模型 

分 类 号：TU311.3[建筑科学—结构工程]