Li Shuangping, Zhang Bin, Zheng Junxing, Wang Dong, Liu Zuqiang
Changjiang Spatial Information Technology Engineering Co., Ltd., Wuhan 430010, China.
School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Sensors (Basel). 2024 Nov 24;24(23):7486. doi: 10.3390/s24237486.
The dimensional quality inspection of prefabricated concrete (PC) elements is crucial for ensuring overall assembly quality and enhancing on-site construction efficiency. However, current practices remain heavily reliant on manual inspection, which results in high operator dependency and low efficiency. Existing Light Detection and Ranging (LiDAR)-based methods also require skilled professionals for scanning and subsequent point cloud processing, thereby presenting technical challenges. This study developed a 3D LiDAR system for the automatic identification and measurement of the dimensional quality of PC elements. The system consists of (1) a hardware system integrated with camera and LiDAR components to acquire 3D point cloud data and (2) a user-friendly graphical user interface (GUI) software system incorporating a series of algorithms for automated point cloud processing using PyQt5. Field experiments comparing the system's measurements with manual measurements on prefabricated bridge columns demonstrated that the system's average measurement error was approximately 5 mm. The developed system can provide a quick, accurate, and automated inspection tool for dimensional quality assessment of PC elements, thereby enhancing on-site construction efficiency.
预制混凝土（PC）构件的尺寸质量检测对于确保整体装配质量和提高现场施工效率至关重要。然而，目前的做法仍然严重依赖人工检测，这导致操作人员依赖性高且效率低下。现有的基于激光雷达（LiDAR）的方法也需要专业人员进行扫描和后续的点云处理，从而带来了技术挑战。本研究开发了一种用于自动识别和测量PC构件尺寸质量的三维激光雷达系统。该系统包括：（1）一个集成了摄像头和激光雷达组件的硬件系统，用于获取三维点云数据；（2）一个用户友好的图形用户界面（GUI）软件系统，该系统结合了一系列使用PyQt5进行自动点云处理的算法。在预制桥柱上进行的现场实验将该系统的测量结果与人工测量结果进行了比较，结果表明该系统的平均测量误差约为5毫米。所开发的系统可为PC构件的尺寸质量评估提供一种快速、准确且自动化的检测工具，从而提高现场施工效率。
