澌溪河水库大坝渗流监测数据研究

Investigation on the Seepage Monitor Data of the Sixihe Reservoir Dam

为了澌溪河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。在水库大坝扩建前,为了防渗的要求,对坝体和坝基进行帷幕灌浆,通过对灌浆前、后压水试验数据和坝后总渗流量监测数据进行分析,表明帷幕灌浆后坝基的平均单位吸水率和坝后总渗流量有明显地减小,比较直观地证实了帷幕灌浆可以达到减小坝基渗流的效果。水库大坝的安全运行期间,为了监控大坝的安全运行和辅助决策,利用人工神经网络建立了有效的渗流量预测模型。计算结果表明,该预测模型能正确地模拟和预测大坝的渗流量。

Investigation on the monitor data of dam is very important to the safety build and running of Sixihe reservoir dam. In the phase efthe dam pre-continuation, make the body and base efdam with purdah grouting to satisfy the request of the seepage defense. Analysis of the experimentation data before grouting and after grouting, then analysis the monitor data of total seepage quality, the results show that, after purdah grouting, the average unit sop- ratio of dam- base and total seepage quality are decrease evidence. It approves that the purdah grouting can effect on the decrease of the seepage of dam- base. In the phase of the dam safety running, aimed to monitor the safety nmning of dam and assistant decision - making, this paper use artificial neural network to build an effect predication model of seepage quality. The computation results show that, this model can simulate and predicate the seepage quality correctly.