Vibrator Rack Pose Estimation for Monitoring the Vibration Quality of Concrete Using Improved YOLOv8-Pose and Vanishing Points

Monitoring the actual vibration coverage is critical for preventing over- or under-vibration and ensuring concrete’s strength. However, the current manual methods and sensor techniques fail to meet the requirements of on-site construction. Consequently, this study proposes a novel approach for estimating the pose of concrete vibrator racks. This method integrates the Linear Spatial Kernel Aggregation (LSKA) module into the You Only Look Once (YOLO) framework to accurately detect the keypoints of the rack and then employs the vanishing point theorem to estimate the rotation angle of the rack without any 3D datasets. The method enables the monitoring of the vibration impact range for each vibrator’s activity and is applicable to various camera positions. Given that measuring the rotation angle of a rack in reality poses is challenging, this study proposes employing a simulation environment to validate both the feasibility and accuracy of the proposed method. The results demonstrate that the improved YOLOv8-Pose achieved a 1.4% increase in accuracy compared with YOLOv8-Pose, and the proposed method monitored the rotation angle with an average error of 6.97° while maintaining a working efficiency of over 35 frames per second. This methodology was successfully implemented at a construction site for a high-arch dam project in China.

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Publication Details

Journal
Buildings
Published
2024-10-05
DOI
https://doi.org/10.3390/buildings14103174
Citations
2
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.52

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article

Vibrator Rack Pose Estimation for Monitoring the Vibration Quality of Concrete Using Improved YOLOv8-Pose and Vanishing Points

Bingyu Ren, Jiajun Wang, Tao Guan, Zheng Xiaofeng
2 citations
Buildings
Structural Health Monitoring Techniques
0.52
article

Vibrator Rack Pose Estimation for Monitoring the Vibration Quality of Concrete Using Improved YOLOv8-Pose and Vanishing Points

Bingyu Ren, Jiajun Wang, Tao Guan, Zheng Xiaofeng
article en
2 citations

Abstract

Monitoring the actual vibration coverage is critical for preventing over- or under-vibration and ensuring concrete’s strength. However, the current manual methods and sensor techniques fail to meet the requirements of on-site construction. Consequently, this study proposes a novel approach for estimating the pose of concrete vibrator racks. This method integrates the Linear Spatial Kernel Aggregation (LSKA) module into the You Only Look Once (YOLO) framework to accurately detect the keypoints of the rack and then employs the vanishing point theorem to estimate the rotation angle of the rack without any 3D datasets. The method enables the monitoring of the vibration impact range for each vibrator’s activity and is applicable to various camera positions. Given that measuring the rotation angle of a rack in reality poses is challenging, this study proposes employing a simulation environment to validate both the feasibility and accuracy of the proposed method. The results demonstrate that the improved YOLOv8-Pose achieved a 1.4% increase in accuracy compared with YOLOv8-Pose, and the proposed method monitored the rotation angle with an average error of 6.97° while maintaining a working efficiency of over 35 frames per second. This methodology was successfully implemented at a construction site for a high-arch dam project in China.

BuildingsVol. 14(10)
Tianjin University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 36%
Structural Health Monitoring Techniques
0.52
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