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作 者:黎松彬 孙啸 祝长江 田正宏[1] LI Song-bin;SUN Xiao;ZHU Chang-jiang;TIAN Zheng-hong(College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China;Sinohydro Seventh Engineering Bureau Co.,Ltd.,Chengdu 610213,China)
机构地区:[1]河海大学水利水电学院,江苏南京210098 [2]中国水利水电第七工程局有限公司,四川成都610213
出 处:《水电能源科学》2025年第4期138-142,132,共6页Water Resources and Power
基 金:国家自然科学基金项目(52279131)。
摘 要:堆石坝碾压密实度检测是筑坝过程中保证施工质量的重要工作,但检测试验时无法进行下一步施工。为避免延误工期,提高压实度检测效率至关重要。针对试验获取体积的灌水法步骤繁琐、耗时、精度存疑的问题,提出一种利用三维激光扫描结合深度学习的方法自动获取试坑体积,该方法以压实度检测规程中的圆形环刀作为训练集,利用环刀与试坑的几何位置关系基于投影法提取试坑点云,再以优化的点云配准算法将试坑顶与试坑内壁拼接得到完整三维试坑,最后基于改进的切片法对试坑点云进行计算获得体积。经验证,该方法只需以较少的训练集便能达到试坑体积自动计算,误差在5%内,处理新试坑单个工人在10 min内可完成,极大地提高了检测效率。The compaction density testing of rockfill dams is a crucial task to ensure construction quality during dam construction.Since the next construction step cannot proceed during testing,improving the efficiency of compaction density testing is essential to prevent delays in the construction schedule.Addressing the issues with the water displacement method for volume measurement,which is complex,time-consuming,and has questionable precision,this paper proposes a method that uses 3D laser scanning combined with neural networks to automatically obtain the volume of test pits.Circular rings from the compaction detection protocol are used as the training set,leveraging the geometric relationship between the rings and the test pits to extract the test pit point cloud based on the projection method.An optimized point cloud registration algorithm then stitches the top of the test pit with the inner wall to obtain a complete three-dimensional model of the pit.Finally,based on an improved slicing method,the volume of the test pit point cloud is calculated.Validation shows that with a relatively small training set,the automatic calculation of test pit volume can be achieved with an error margin within 5%.A single worker can process a new test pit in 10 minutes,significantly improving detection efficiency.
分 类 号:TV522[水利工程—水利水电工程]
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