Overtime warning of concrete pouring interval based on object detection model
MEI Jie1, LI Qingbin1, CHEN Wenfu2, WU Kun2, TAN Yaosheng2, LIU Chunfeng2, WANG Dongmin1, HU Yu1
1. Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China; 2. China Three Gores Projects Development Co., Ltd., Chengdu 610041, China
Abstract：Timely, comprehensive and accurate access to the status and progress of various activities on the construction site is essential for quality control, progress tracking and productivity analysis, and is also necessary for the full realization of fine management and intelligent construction. At present, the progress recording and quality control under the concrete pouring construction scenario are still mostly done manually, leading to problems such as insufficient timeliness, misreporting and omission. In this study, the semantic segmentation and object detection technology in the field of deep learning computer vision are applied to the field of engineering construction. Real-time construction progress is obtained by identifying formwork cover ratios and the unloading event of the bucket, and the overtime warning of layer coverage time with second-level accuracy is realized.
梅杰, 李庆斌, 陈文夫, 邬昆, 谭尧升, 刘春风, 王东民, 胡昱. 基于目标检测模型的混凝土坯层覆盖间歇时间超时预警[J]. 清华大学学报（自然科学版）, 2021, 61(7): 688-693.
MEI Jie, LI Qingbin, CHEN Wenfu, WU Kun, TAN Yaosheng, LIU Chunfeng, WANG Dongmin, HU Yu. Overtime warning of concrete pouring interval based on object detection model. Journal of Tsinghua University(Science and Technology), 2021, 61(7): 688-693.
2021, Vol. 61 
