Research on Deep Convolutional Neural Network in Damage Identification of Truss Structure

Abstract Aiming at the problem of damage identification inside the truss, through the convolutional neural network, after a large amount of data simulation, the deep learning convolutional neural network can effectively identify the internal damage of the truss and accurately determine the damage lo...

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Bibliographic Details
Published inIOP conference series. Earth and environmental science Vol. 791; no. 1; pp. 12033 - 12037
Main Authors Gao, Yiting, Yang, Xiaolin
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.06.2021
Subjects
Artificial neural networks
Damage detection
Data simulation
Data transmission
Imports
Neural networks
Trussed structures
Trusses
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Summary:Abstract Aiming at the problem of damage identification inside the truss, through the convolutional neural network, after a large amount of data simulation, the deep learning convolutional neural network can effectively identify the internal damage of the truss and accurately determine the damage location as well as the damage recognition and effective prediction of other large roof trusses. First, we import the existing data into the convolutional neural network for identification, and calculate the damage identification process belonging to the truss. Then, we import another part of the data to verify the practicability and accuracy of the convolutional neural network, and obtain a series of data streams.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/791/1/012033