适于隔震结构的两阶段实时子结构试验方法

Two-stage real-time hybrid testing method for isolated structures

为在试验中同时模拟隔震结构中隔震层和被隔震结构的非线性,提出一种适于隔震结构的两阶段实时子结构试验方法。第一阶段先将隔震支座单独进行物理试验,通过试验观测数据训练神经网络,使其可以准确拟合隔震支座动力特性;第二阶段基于训练好的神经网络建立隔震层的数值子结构模型,与被隔震结构进行实时子结构试验,完成对隔震结构的动力性能测试。数值仿真中该方法与整体模型仿真结果的峰值误差在3%以内,试验验证中该方法与整体结构振动台试验的峰值误差在6%以内。数值仿真和试验对比表明:提出的两阶段实时子结构试验具有良好的精度。该方法避免了在振动台试验中由于缩尺导致隔震支座受到欠质量的影响,充分保证其力学性能的真实性。同时有效解决了在利用实时子结构试验对各部分都为强非线性的隔震结构进行试验测试时,由于数值子结构建模不准确导致的试验误差问题。为隔震结构的抗震性能测试提供了新的试验方法。

To simulate the nonlinearity of isolation layer and isolated structure simultaneously in seismic testing,this paper proposes a two-stage real-time hybrid testing method for isolated structures.In the first stage,the isolation bearing was tested separately,and the neural network was trained by the test data for fitting the dynamic characteristics of the isolation bearing.In the second stage,the trained neural network was used to build the numerical substructure model of isolation layer,which was then combined with the isolated structure to realize realtime hybrid testing(RTHT),so as to complete the dynamic performance test of the overall isolated structures.In numerical simulation,the peak error of the results between the proposed method and overall model simulation was within 3%,while in experimental verification,the peak error of the results between the proposed method and shaking table testing of overall structures was within 6%.Numerical simulation and experimental comparison show that the proposed two-stage real-time hybrid testing has a good accuracy.It avoids the influence of insufficient mass of isolation bearing caused by reduced scale in shaking table testing,and ensures the authenticity of its dynamic performance.Besides,it can solve the errors caused by inaccurate modeling of numerical substructure when using RTHT to test the isolated structures with strong nonlinearity in each part.The two-stage real-time hybrid testing provides a new method for seismic testing of isolated structures.