BP NEURAL NETWORK MODELING OF A MAGNETORHEOLOGICAL DAMPER

摘要：

Magnetorheological (MR) dampers are regarded as one of the most promising devices in vibration mitigation of civil structures against severe earthquakes and strong winds. To implement vibration control via MR dampers,dynamic models that can accurately capture the dampers inherent nonlinear behaviors should be developed. In the present paper,using the results of mechanical property tests of a MR damper,both forward and inverse models of the damper are developed based on back propagation (BP) neural networks,respectively. In addition,the generalization ability of the two neural network models is validated,and the sensitivities are analyzed on the assumption that noise arises from additive and multiplicative perturbations.

作者: Zhen Mei Jianbing Chen Jie Li Jia Jia

作者单位: State Key Laboratory of Disaster Reduction in Civil Engineering,Tongji University,Shanghai 200092,P. Shanghai Land Sea Architecture Technology Co.,Ltd.,Shanghai 201203,P.R.China

会议类型: 国际会议

会议名称: The International Symposium on Innovation & Sustainability of Structures in Civil Engineering(2011年土木工程结构创新与可持续发展国际会议)

会议地点: 厦门

会议语种:英文

页码: 1314-1320

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）