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作 者:彭方圆 PENG Fangyuan(BUCG REAL ESTATE Co.,Ltd.,Beijing 100081,China)
机构地区:[1]北京城建房地产开发有限公司,北京100081
出 处:《粉煤灰综合利用》2024年第1期113-118,共6页Fly Ash Comprehensive Utilization
摘 要:以保障工程施工安全为目的,提出综合楼施工深基坑变形多点视觉监测方法。以某待测综合楼施工工程深基坑项目为研究标靶,在其周围设置测点并布设图像传感器采集深基坑支护桩顶、周围道路、管线等位置的相关图像,利用包围盒法重建三维深基坑图像,采用粗糙K均值聚类算法计算靶点范围与中心,通过对比原始图像与监测图像的标志点差异获取深基坑的变形位移值,利用所得深基坑图像的标志点位移变化量构建监测数据样本,通过训练RBF神经网络输出深基坑变形预测结果。实验结果表明:该方法可有效监测深基坑变形;深基坑周围道路沉降的变形量最大约为15.12 mm,未达到报警值40 mm;围护加固结构可有效约束深基坑变形。A multi-point visual monitoring method for deformation of deep foundation pits in comprehensive building construction is proposed with the aim of ensuring construction safety.Taking a deep foundation pit project of a comprehensive building construction project to be tested as the research target,measuring points are set up around it and image sensors are deployed to collect relevant images of the top of the deep foundation pit support pile,surrounding roads,pipelines,etc.The three-dimensional deep foundation pit image is reconstructed using the bounding box method.The rough K-means clustering algorithm is used to calculate the range and center of the target points.The deformation displacement value of the deep foundation pit is obtained by comparing the difference between the original image and the monitoring image's landmark points,Construct monitoring data samples using the displacement changes of landmark points in the obtained deep foundation pit images,and output deformation prediction results of deep foundation pits through training an RBF neural network.The experimental results show that this method can effectively monitor the deformation of deep foundation pits;The maximum deformation of the road settlement around the deep foundation pit is about 15.12mm,which has not reached the alarm value of 40mm;The reinforcement structure of the enclosure can effectively constrain the deformation of deep foundation pits.
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