Classification of Multistates of Internal Damage in Concrete Based on Convolutional Neural Network Analysis of Time-Frequency Images-Reference-Cited by-同舟云学术

Classification of Multistates of Internal Damage in Concrete Based on Convolutional Neural Network Analysis of Time-Frequency Images

Published:2022-12 Issue:6 Volume:36 Page:
ISSN:0887-3828
Container-title:Journal of Performance of Constructed Facilities
language:en
Short-container-title:J. Perform. Constr. Facil.

Author:

Shang Gao¹,Chen Jun²^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil Engineering, School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China.

2. Professor, Dept. of Civil Engineering, School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CF.1943-5509.0001771

Reference35 articles.

1. ASTM. 2016. Standard test method for pulse velocity through concrete. West Conshohocken, PA: ASTM International.

2. Time–frequency decomposition-assisted improved localization of proximity of damage using acoustic sensors

3. Notes on convolutional neural networks;Bouvrie J.;Practices,2006

4. Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks

5. The impact-echo response of concrete plates containing delaminations: numerical, experimental and field studies

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