Research On The Multi-source Data Fusion Model For Leakage Monitoring Of High Filled Channel Of South-to-north Water Transfer Project

High fill channels are widely used in long distance water transfer project in China.Because of long distance water transfer project wide distribution,engineering geological condition is complex,can appear high fill channel local ground subsidence,landslide,frost heave,such as the lining panel craze,impervious body was pulled and cause water seepage(leak).However,because the canal is longer,leakage would still be bigger.High fill section channel once leakage for a long time will cause bursts,will directly affect the life property safety of the residents along the road.Therefore,high fill canal section of the seepage monitoring technology is one of the key technology in long distance water transfer project safety monitoring.To ensure the safe operation of water after the channel to ensure that people's life and property security,need for special seepage monitoring of high fill canal section design.Special structure makes the seepage monitoring more difficult,need to choose more suitable for the leakage monitoring methods and techniques.In fact,when the high fill channel leakage,leakage area will produce a environmental quantities such as temperature and humidity and seepage field anomaly area.Therefore,real-time monitoring and leakage associated with a variety of environmental quantity and mutation characteristics for multi-source data fusion will be more meaningful.In this paper.The leakage monitoring sensor network hardware design,multi-source data fusion model validation and monitoring information visualization platform implementation to carry on the research and design,its main content is as follows:1)To study the mechanism of high fill channel leakage hidden trouble,looking for high fill channel leakage detection of commonly used method,adopt multiple sensors to detect leakage of high fill channel condition.The design can be used for high fill channel leakage detection of Internet monitoring platform,can sense the temperature field and humidity field,seepage field and moisture content of the information such as current changes.2)Based on kalman-RBF high fill channel leakage monitoring of multi-source data fusion model,implement the predetermined leakage leakage level of recognition and classification;Probability of the model combined with kalman filter and RBF neural network,the monitoring of multi-source data through the network training can effectively realize the classification of the leakage level.3)Using Labview graphical programming software to remote data visualization platform design,realized the high fill channel leakage monitoring results real-time display and forecast analysis,and through the experimental model to verify the effectiveness of the monitoring system.Finally the practical application in Xin Xiang People's Victory Canal high fill channel leakage monitoring.