Description
Falling-off of the external walls on high-rise building had occurred frequently in recently years, which caused the property damage or personal casualties and endanger urban public safety. A method using 3D laser scanning technique was studied for the detection of potential safety hazards such as hollowing and falling-off of building external walls. Based on the point cloud data, especially the z-coordinate values of the point cloud data, the identification criteria for the safety hazards such as hollowing and falling-off was established, and a precise hazard identification algorithm was developed and applied to quantitative detection of building external walls. The detection results were compared with that of the infrared thermal imaging to verify the identification ability for hazards with different positions or sizes. Fixed targets were arranged near the external wall to collect the point cloud data regularly, and the flatness model of the entire external wall was established. Then, the variation characteristics of the hollow area and height with time were analyzed based on contour lines generated from the flatness model, which would provide technical basis for the assessment and monitoring of falling-off hazard of external wall. The research results show that the proposed 3D laser scanning technique can precisely identify the falling-off hazards of the external wall.
