共查询到19条相似文献,搜索用时 156 毫秒
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中小型水库管理单位进行渗流监测资料分析比较少,开展大坝安全监测工作时间不太长,大部分水库没有系统的大坝安全监测分析软件。用大众化电子表格Excel进行基本的回归分析,建立渗流安全监测统计模型,用测压管水位变化趋势和特征测压管位势理论,定量地判断测压管水位是否异常变化,判断大坝安全运行状况,给水库管理单位提供可靠的安全监测技术资料。 相似文献
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龙凤山水库大坝测压管安全监测系统更新工程,将通过用遥测、通信和计算机等先进技术对大坝安全监测系统实现全天候远程自动监测,实时监测坝体和坝基的渗流压力,观测坝体的渗流压力分布情况和浸润线位置以及坝基渗流压力分布情况,统计分析测压管数据变化过程,对保证水库大坝安全运行,发挥水库枢纽工程效益有着十分重要的意义。 相似文献
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根据光华水库2013~2019年测压管的渗流观测数据,分析测压管水位与库水位过程线变化规律,结合测压管水位与库水位相关性分析,对大坝运行过程中的渗流情况作出评价,并找出大坝运行存在的问题.对水库大坝安全监测资料的分析和水库运行管理有一定的参考价值. 相似文献
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许多20世纪60~70年代修建的水库、大坝安全监测项目得到更新完善.在土石坝监测系统的改造中,渗流监测是土石坝安全监测中的重点,推荐使用测压管方式监测;变形监测可采用引张线、垂线系统.混凝土坝的监测重点是变形监测,引张线、垂线是常用方式.混凝土坝渗流监测主要是扬压力、渗流量监测.大坝安全监测实现数据采集和处理自动化是实现水库和大坝运行管理现代化的必然趋势.自动化系统能否成功,关键在设计和选型上. 相似文献
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大坝渗流安全监测技术研究 总被引:5,自引:0,他引:5
针对目前大坝渗流安全监测仪器和监测方法存在的技术问题,为了避免造成观测成果的滞后和失真,对大坝渗流监测中的关键设备,即测压管和渗压计的监测效果,从理论与实践的结合上进行了分析研究,提出了具体的改进意见和建议。 相似文献
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赫振平 《水电自动化与大坝监测》2009,33(1):51-53
在不需要增加水库除险加固工程投资的情况下,对土石坝安全监测中的测压管灵敏度检验规范的要求进行了改进,从而增加了渗流监测可供研究的数据,并通过对试验数据的定量分析,了解土石坝的填筑质量以及运行过程中坝体的稳定性,拓展了大坝安全监测分析的渠道. 相似文献
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渗流特性是反映土石坝运行性态的重要内容。依据万安水电站土石坝坝体测压管渗压水位监测资料,从渗压水位变化过程、渗压水位与上游水位相关性、坝体浸润线和心墙渗透坡降等方面,对大坝渗流特性与渗流状态进行了分析与评价。研究表明,万安水电站土石坝坝体渗压水位变化规律和坝体浸润线状态合理,心墙防渗效果较好,坝体渗流特性正常。 相似文献
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针对土石坝渗透参数和测压管水位间复杂的非线性关系,应用最小二乘支持向量机于土石坝渗透系数的反演。首先利用有限元模型得到最小二乘支持向量机的训练样本,建立坝体水压分量相对值和渗透系数间复杂的非线性关系,并将其输入到训练好的最小二乘支持向量机模型,即可得到大坝渗透系数的反演值。以某土石坝为例经对比分析,该方法是可行的。 相似文献
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Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine (SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam. Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution. 相似文献
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Extreme hydrological events induced by typhoons in reservoir areas have presented severe challenges to the safe operation of hydraulic structures. Based on analysis of the seepage characteristics of an earth rock dam, a novel seepage safety monitoring model was constructed in this study. The nonlinear influence processes of the antecedent reservoir water level and rainfall were assumed to follow normal distributions. The particle swarm optimization (PSO) algorithm was used to optimize the model parameters so as to raise the fitting accuracy. In addition, a mutation factor was introduced to simulate the sudden increase in the piezometric level induced by short-duration heavy rainfall and the possible historical extreme reservoir water level during a typhoon. In order to verify the efficacy of this model, the earth rock dam of the Siminghu Reservoir was used as an example. The piezometric level at the SW1-2 measuring point during Typhoon Fitow in 2013 was fitted with the present model, and a corresponding theoretical expression was established. Comparison of fitting results of the piezometric level obtained from the present statistical model and traditional statistical model with monitored values during the typhoon shows that the present model has a higher fitting accuracy and can simulate the uprush feature of the seepage pressure during the typhoon perfectly. 相似文献
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柴河水库大坝右坝段坝基存在渗漏问题,为了水库大坝的安全建设和运行对大坝监测数据进行研究非常重要。采用逐步回归分析法对大坝坝基测压管多年监测数据建立了统计回归分析模型,计算结果表明,观测值与拟合值统计复相关系数较大,估计标准误差较小,模型有效地反映了坝基渗流的变化规律和发展趋势。为了监控大坝的安全运行和辅助决策,利用小波神经网络建立了有效的坝基渗流量预测模型,计算结果表明,该预测模型收敛速度较快、预测精度较高,能正确地模拟和预测大坝的渗流量。 相似文献