Truss Damage Identification Based on Joint Multiple Reconstructions Autoencoders
Aiming at the problems that were difficult to capture the damage feature information and the identification results were inaccurate when there were different types of damages in truss rod elements,a damage identification method was proposed using JMRAE.Firstly,JMRAE was applied to intercept the signals according to different scale numbers,and the Sigmoid function and ReLU function were combined to extract the features.ZCA was introduced to reduce the features'dimension to retain important information and reduce data redundancy.Then,SoftMax classifier was applied to solve the local features of different segments in the hidden layers,and feature fusion was performed to determine the structural states.Finally,the numerical three-dimensional truss structure model and the laboratory-built truss were used for validation and comparative study with the refined composite multiscale dispersion entropy(RCMDE),kurtosis,and back-propagation(BP)neural network meth-ods.The results show that the proposed method has higher damage identification accuracy.
万方数据
维普
