摘要
本文首先通过一根预应力钢筋混凝土 (PRC)梁振动测试实验 ,证实了PRC梁的弯曲振动自振频率随着预应力的降低而有所增加 ,其规律与受轴压力梁的自振频率受轴力的影响基本一致 ,因此采用受轴压力梁的模型作为PRC梁的计算模型 ,然后针对试验梁的情况 ,通过比较选择合适的边界条件模型 ,并采用神经网络方法 ,识别其边界条件的参数 ,在此基础上 ,再用神经网络识别预应力损伤 ,通过数值模拟和实测数据分析得到 ,通过振动测试用神经网络是可以识别PRC梁的预应力损失的。
It is first verified by the vibration test of a prestressed reinforced concrete(PRC) beam that the natural frequencies of the beam decrease with the increasing of prestress level.The case of prestressing force in beam is consistent with the beam suffered from axial force,thus a prestressed reinforced beam model is then built,similar to the model of a reinforced beam under axial force.The appropriate boundary conditions of the mode are supposed and the boundary parameters are then identified by use of neural network.On this base,after analyzing simulation and measured data,prestress loss can be identified.
出处
《振动与冲击》
EI
CSCD
北大核心
2003年第3期95-97,共3页
Journal of Vibration and Shock