Structural damage identification monitoring method based on vibration signal space real-time recurrent graph convolutional neural network

Abstract

The invention provides a structural damage identification monitoring method based on a vibration signal space real-time recurrent graph convolutional neural network. The method comprises the followingsteps: S1) establishing a numerical model and generating external excitation such as wind excitation load; S2) preparing structure numerical models of different damage positions and damage degrees, and loading wind excitation load and other excitation to the numerical models; S3) generating a corresponding recurrence plot sample according to the time-history acceleration response; and S4) training and testing the convolutional neural network of the sample. The method has the advantages that the method is used for carrying out lossless damage identification on a structure in the field of civilengineering, a corresponding recursive graph generated by acceleration responses of multiple points on the structure is proposed to serve as an analysis object, and feature extraction is carried outby adopting a convolutional neural network. Compared with a traditional machine learning algorithm, the convolutional neural network has congenital advantages in feature extraction of two-dimensionaland above high-dimensional data, the training efficiency and generalization ability of the convolutional neural network in structural damage recognition can be effectively improved, and the convolutional neural network has good precision and low training cost.

Description

technical field [0001] The invention relates to the technical fields of structural health monitoring and artificial intelligence, in particular to a structural damage identification and monitoring method based on a vibration signal space-time recursive graph convolutional neural network. Background technique [0002] At present, structural damage monitoring is divided into structural local damage monitoring and structural overall damage monitoring. Structural local damage monitoring is to use sensors or manual methods to check the safety status of structural local components; structural overall damage monitoring is to use structural displacement, natural frequency, vibration mode, modal curvature, etc. Performance is evaluated. Structural overall damage monitoring can better reflect the performance of the structure, and it can also better evaluate the overall safety level of the structure for the structural management unit. [0003] Traditional damage identification algori...

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Problems solved by technology

For complex structures, relevant theoretical derivations will greatly increase the threshold for using this method, and structural damage often affects its fundamental frequency, mode, and modal curvature at the same time, so it is very difficult to identify damage based solely on certain dynamic characteristics. It is difficult to obtain better accuracy, and these characteristics are often disturbed and distorted during the extraction process, and the accuracy of damage identification results needs to be improved

[0004] On the basis of the traditional loss identification algorithm, the use of relatively primitive acceleration response time history data can better avoid the loss of information, but the time history data is not very direct for the display of dynamic characteristics, and it also has defects

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