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Hybrid Modeling for Structural Dynamics of Complex Systems Based on Neural Network

机译:基于神经网络的复杂系统结构动态的混合建模

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To vibration isolation system composed of four wire ropes for the study, and a hybrid modeling method was adopted which neural network mode and a priori knowledge model are connected in series. Multi-DOF hybrid neural network model is established. A method of determining indirectly restoring force of isolation system by the experimental data was proposed through the establishment of the rigid body dynamics equation of vibration isolation system. Through the network training, the neural network model to describe the restoring force characteristics of the four wire rope isolator was established. The simulation results show that the hybrid neural network modeling method has the advantages of high precision, small amount of the training sample data and the modeling cycle is short, etc. Hybrid model contains the physical parameters of the system, and it is very convenient to analyze the effect of parameters.
机译:对于该研究的四根线绳组成的振动隔离系统,采用混合建模方法,其中神经网络模式和先验知识模型串联连接。建立多DOF混合神经网络模型。通过建立振动隔离系统的刚体动力学方程,提出了通过建立实验数据来确定隔离系统间接恢复力的方法。通过网络训练,建立了神经网络模型来描述四根线绳隔离器的恢复力特性。仿真结果表明,混合神经网络建模方法具有高精度,少量训练样本数据和建模周期的优点。混合模型包含系统的物理参数,它非常方便分析参数的效果。

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