摘要
针对高土石坝变形监控模型主要基于单一测点,无法定量考虑测点空间关联性的问题,构建了基于Vine-Copula的变形监控模型,并提出了基于蒙特卡洛随机抽样法的空间置信域预警阈值设置方法。在模型构建过程中,充分考虑了多测点之间的时序特性和空间相关性,利用Vine-Copula方法对变形数据进行精确建模和分析,以揭示高土石坝变形的整体趋势。同时,通过蒙特卡洛随机抽样法确定了空间置信域,为预警阈值的设定提供了科学依据。工程实践表明:该模型模拟结果能够准确反映高土石坝变形的整体趋势,具有较高的合理性和精度,有效实现了监测效应量向高土石坝空间全域的拓展。研究成果可为高土石坝安全监控提供新的思路和方法,具有重要的理论意义和实践价值。
Aiming at the problem that the deformation monitoring model for high earth-rock dams is mainly based on a single measuring point and cannot quantitatively consider the spatial correlation of measuring points,a deformation monitoring model based on Vine-Copula was constructed,and a spatial confidence domain early warning threshold setting method based on Monte-Carlo random sampling method was proposed.In the process of the model construction,the time series characteristics and spatial correlation between multiple measuring points were fully considered,and the Vine-Copula method was used to accurately model and analyze the deformation data to reveal the overall trend of high earth-rock dam deformation.At the same time,the spatial confidence region was determined by Monte-Carlo random sampling method,which provided a scientific basis for the setting of early warning threshold.The engineering practice showed that the model simulation results can accurately reflect the overall deformation trend of high earth-rock dam,with high accuracy and rationality,and effectively realize the expansion of monitoring effect-quantity to the whole space of high earth-rock dams.The research results can provide new ideas and methods for the safety monitoring of high earth-rock dams,and have important theoretical significances and practical values.
作者
陈天赐
李艳玲
张芳
陈枭
CHEN Tianci;LI Yanling;ZHANG Fang;CHEN Xiao(State Key Laboratory of Hydraulics and Mountain River Engineering,Sichuan University,Chengdu 610065,China;College of Water Resources and Hydropower,Sichuan University,Chengdu 610065,China;Power China Guiyang Engineering Corporation Limited,Chengdu 610065,China;Zhenxiong County Water Bureau,Zhaotong 657200,China)
出处
《人民长江》
北大核心
2024年第5期206-212,218,共8页
Yangtze River
基金
国家重点研发计划项目(2018YFC0407103)。