实景三维下的AIGC变形监测算法分析

Analysis of AIGC deformation monitoring algorithm in real 3D environment

针对建筑工程变形监测中对地下结构变形认知缺乏综合性、系统性的问题,提出了一种人工智能变形监测AIGC算法。该算法以BIM为基础架构,融合三维点云技术,通过三维模型建立和更新、图像处理技术和布尔沙模型,构建了一个模拟仿真空间实体,利用已知数据集进行模型训练,人工智能生成地下结构的高精度姿态与位移结果,实现了对实景三维场景中地下结构的变形进行准确表示、定量分析和实时监测,具有较高的时效性和准确性。经过广州市鸦岗基坑支护项目实际试验,结果表明:该算法减少了对近位勘察的需求,进一步挖掘出大量高质量的变形数据,有效发现了地下结构中重点、难点部位的深层水平位移特征,为建筑工程整体稳定性的调查、检测、验算、分析和安全性评定等活动提供了重要的方法依据。

Aiming at the lack of comprehensive and systematic understanding of underground structure deformation in construction engineering deformation monitoring,an artificial intelligence deformation monitoring AIGC algorithm is proposed.This algorithm is based on BIM architecture and integrates 3D point cloud technology.Through the establishment and updating of 3D models,image processing techniques,and Bursa model,a simulated spatial entity is constructed.The model is trained using known datasets,and high-precision pose and displacement results of underground structures are generated by artificial intelligence.It achieves accurate representation,quantitative analysis,and real-time monitoring of deformation of underground structures in real-world 3D scenes,Has high timeliness and accuracy.After the actual test of the Yagang foundation pit support project in Guangzhou,the results showed that the algorithm reduced the need for near field exploration,further excavated a large amount of high-quality deformation data,effectively discovered the deep horizontal displacement characteristics of key and difficult parts in underground structures,and provided important methodological basis for the investigation,detection,verification,analysis,and safety evaluation of the overall stability of building engineering.