DAMAGE IDENTIFICATION OF BEAM STRUCTURE BASED ON HYBRID NEURAL GENETIC ALGORITHM - WANG MingYue; MIAO BingRong; Li XuJuan; YANG ZhongKun (Jixie qiangdu)
It has established that a crack has an important effect on the dynamic behavior of a structure.To identify the location and depth of a crack on a structure,a method is presented which uses hybrid neuro-genetic technique.This method combines genetic algorithm（GA） with neural network,and uses genetic algorithm to optimize the BP network.Though the finite element analysis,acquire the first three natural frequencies of the beam,which used as inputs into neural network models for damage assessment.Genetic algorithm（GA） optimizes the weights and thresholds of the network,and using the optimization results as the initial value of the three layer BP neural network.Though the training of the sample data,then establish the suitable network.Finally,using the theoretical natural frequencies as the test values,obtain the predicted results of crack parameters.Comparing the theoretical value with the predicted value,the results show that this algorithm can identify the damage structure accurately.