基于神经网络的多孔泡沫金属磁流变液阻尼器模型

A Neural Network Model of Porous Metal Foam Magnetorheological Fluid Damper

多孔泡沫金属磁流变液阻尼器是采用泡沫金属储存磁流变液的新型阻尼器。通过磁流变阻尼器的性能试验研究,得到了阻尼力与电流之间的关系,采用BP神经网络,建立了磁流变阻尼器正向模型。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,证明了该方法的有效性,与已有的模型相比,具有精度高,计算简便等特点。

Porous metal foam magnetorheological fluid damper is a new damper using the foam metal storage of the MRF. By MR damper performance test,we studied the relationship between the damping force and different currents,a magneto-rheological damper forward model is set up by BP neural network. Simulation results show that the neural network model can accurately predict the MR damper damping force and control current,and it also proves the effectiveness of this method. Compared with the existing model,the calculation is simple with high accuracy.