神经网络在悬索桥故障诊断中的应用

Application of Artificial Neural Network in Cable Suspension Bridge Breakdown Diagnosis

利用改进的反向传播神经网络BP(back propagation)控制方法,结合压电陶瓷(PZT)受力变形时电压电场变化的机理,通过对悬索桥梁的应力应变进行在线检测,对桥梁结构健康状态进行智能诊断。通过实验研究获得了大量的实验数据,证明了该方法的可行性、先进性,为实际应用奠定了理论与实验基础。

By using improved back propagation artificial neural network control method, combined with the mechanism of voltage electrical field change when force was applied on piezoceramics（PZT） resulting in deformation, via on-line test for press and strain of cable suspen- sion bridges, carries out intelligent diagnosis for bridges＇ structural health state. And through experimental studies, a lot of experimental data had been obtained, in the meantime the method was approved with feasibility, advancement, having laid a foundation of theory and experiment for practical application.