基于计算机视觉的预制墙板临时支撑安全合规性检查

预制构件安装过程中临时支撑的安全合规性对装配式施工安全至关重要，对其进行自动检查并辅助施工安全监控具有重要意义。以最为常见且具有代表性的预制混凝土墙板为例，利用 YOLO-v5 网络构建了预制墙板及其临时支撑的自动识别模型，进而提出了预制墙板临时支撑的安全合规性自动检查方法。测试结果表明，该识别模型的平均精度均值达到 95.3%，在充分考虑施工现场不利因素情况下检查方法的准确率达到 70.7%，证实了该方法的有效性和可行性。 这不仅可以提升预制墙板安装的安全性，而且还可为其他类型预制构件安装的合规性检查提供参考。

Computer Vision-Based Safety Compliance Checking for theTemporary Support of Precast Walls

The safety compliance of temporary supports during the erection of prefabricated components is of importance toprefabricated construction， it’s quite meaningful to carry out automatic checking of the compliance and assist construction safetymonitoring． Taking commonly-seen and representative precast concrete walls as an example， this research establishes an objectdetection model for precast walls and relevant temporary supports based on YOLO-v5 network， and further proposes an automatedsafety compliance checking method for the temporary support of precast walls． It is shown from a test that the mean AveragePrecision（ mAP） of the detection model is up to 95.3%， and the accuracy of the checking method is 70.7% under a harsh constructionenvironment， showing the validity and feasibility of the proposed method． This research， thus， not only improve the safety level ofthe erection of precast walls， but also provide a reference for the safety compliance checking of other precast components.