Post-Earthquake Damage Detection of Reinforced Concrete Members Based on the Improved YOLO Model

CHEN Zixiao; SONG Chenghao; HU Xiaobin

doi:10.3724/j.gyjzG25071002

Volume 55 Issue 7

Jul. 2025

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CHEN Zixiao, SONG Chenghao, HU Xiaobin. Post-Earthquake Damage Detection of Reinforced Concrete Members Based on the Improved YOLO Model[J]. INDUSTRIAL CONSTRUCTION, 2025, 55(7): 143-151. doi: 10.3724/j.gyjzG25071002

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CHEN Zixiao, SONG Chenghao, HU Xiaobin. Post-Earthquake Damage Detection of Reinforced Concrete Members Based on the Improved YOLO Model[J]. INDUSTRIAL CONSTRUCTION, 2025, 55(7): 143-151. doi: 10.3724/j.gyjzG25071002

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Post-Earthquake Damage Detection of Reinforced Concrete Members Based on the Improved YOLO Model

doi: 10.3724/j.gyjzG25071002

School of Civil Engineering, Wuhan University, Wuhan 430072, China

Received Date: 2025-07-10
Available Online: 2025-09-12

Abstract

Abstract

In this paper， seismic tests of reinforced concrete （RC） column were conducted， based on which the post-earthquake damage dataset of RC member was established considering the additional data obtained externally. A lightweight model， i.e. FG-YOLOv5， was then proposed by replacing the backbone of YOLOv5 model with the FasterNet network and introducing the C3Ghost module and GhostConv in the neck of YOLOv5 model. Based on the dataset， the FG-YOLOv5 model was trained and tested and the ablation test was also carried out. Finally， the model was deployed on a smartphone to achieve rapid post-earthquake damage detection of RC members. The results showed that， compared to the conventional convolution， the partial convolution and GhostConv can greatly reduce the computational cost. By introducing the FasterNet， C3Ghost module and Ghostconv into the YOLO v5 model， greatly smaller model size and computation with a bit higher detection accuracy can be achieved. The FG-YOLOv5 model proposed in this paper can be conveniently deployed on mobile phones for rapid post-earthquake damage detection of RC members.
- reinforced concrete member,
- post-earthquake damage,
- fast detection,
- YOLO model,
- lightweight

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References(27)

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