摘要
房屋建筑老化与极端气候频发导致建筑结构损伤问题日益加剧,传统的加固与改造方法效率低下且精度欠佳。针对该问题,文章提出了一种基于计算机视觉技术的建筑结构加固与改造方法,通过无人机与高分辨率摄像设备获取建筑物的外观和内部结构图像数据,结合深度学习算法,自动识别结构损伤,并生成精确的三维模型。实验结果表明,该方法显著提升了结构加固设计精度与效率,减少了人工干预,能够有效应对复杂的建筑加固需求。
With the aging of buildings and the frequent occurrence of extreme weather conditions,the problem of structural damage in buildings is becoming increasingly prominent,and traditional reinforcement and renovation methods are facing challenges such as low efficiency and insufficient accuracy.This article proposes a method for strengthening and renovating building structures based on computer vision technology.This method utilizes drones and high-resolution cameras to obtain image data of the appearance and internal structure of buildings.Combined with deep learning algorithms,it automatically identifies structural damage and generates accurate 3D models.The experimental results show that this method significantly improves the accuracy and eficiency of structural reinforcement design,reduces manual intervention,and can effectively respond to complex building reinforcement needs.
作者
吕媛媛
LV Yuanyuan(Weifang Binhai Engineering Testing Co.,Ltd.,Weifang 262737,China)
关键词
计算机视觉
结构加固
深度学习
computer vision
structural reinforcement
deep learning
