The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2023.01406109
PDF

Damage Security Intelligent Identification of Wharf Concrete Structures under Deep Learning and Digital Image Technology

Author 1: Jinbo Zhu
Author 2: Yuesong Li
Author 3: Pengrui Zhu

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 6, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Artificial Intelligence (AI) technology has quickly developed under the mighty computing power of computers. At this stage, there are many mature non-destructive testing methods in civil engineering, but they are generally only suitable for simple structures and evident damage characteristics. Therefore, it’s necessary for us to investigate the damage identification of wharf concrete structures under deep learning and digital image technology. The article propose a damage detection and localization method based on Neural Network (NN) technology in deep learning and Digital Image Correlation (DIC) to identify internal damage to concrete used for wharf construction. Firstly, the identification model of concrete structure is constructed using NN technology. Then, structural damage identification of concrete is further investigated using DIC. Finally, relevant experiments are designed to verify the effect of the model. The results show that: (1) The damage model of concrete structure constructed by NN technology has high convergence and stability and can control the test error well. (2) The image output by the DIC equipment is processed and input into the NN. The errors of the various parameters of different concretes can be within the acceptable range. This paper aims to provide good ideas and references for follow-up structural health monitoring and other topics and has significant engineering application value.

Keywords: Structural damage identification; deep learning; neural network; digital image; concrete

Jinbo Zhu, Yuesong Li and Pengrui Zhu, “Damage Security Intelligent Identification of Wharf Concrete Structures under Deep Learning and Digital Image Technology” International Journal of Advanced Computer Science and Applications(IJACSA), 14(6), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01406109

@article{Zhu2023,
title = {Damage Security Intelligent Identification of Wharf Concrete Structures under Deep Learning and Digital Image Technology},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01406109},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01406109},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {6},
author = {Jinbo Zhu and Yuesong Li and Pengrui Zhu}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Computer Vision Conference (CVC) 2026

16-17 April 2026

  • Berlin, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2025

19-20 June 2025

  • London, United Kingdom

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2025

6-7 November 2025

  • Munich, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org