临江岸坡安全监测信息系统开发及监控模型研究

发布时间：2018-11-19 20:45

【摘要】：岸坡治理在防洪、灌溉、供水、航运、水保等方面发挥了巨大的社会效益、经济效益和环境效益,在国民经济建设和社会安全保障中起到了巨大作用。岸坡安全监测依据对监测仪器产生的时序数据分析处理来揭示岸坡的工作状态,保障其安全运行,在岸坡治理中发挥着重要作用。一般情况下,为了充分了解岸坡运行状态,在岸坡上布置了较多的监测点及监测项目,监测点空间分布也较广,构成了复杂的空间监测体系,产生了大量监测数据,基于以上问题,本论文研究开发岸坡安全监测信息系统,实现了岸坡安全监测的系统化管理。基于GIS平台,分别应用TIN表面和栅格表面建立临江岸坡可视化模型,通过三维建模软件Sketchup给栅格表面加上纹理,使其更加直观。构建了岸坡监测数据库对雨量、位移、渗压等监测信息进行有效管理。基于监测数据,构建BP神经网络模型和GM(1,1)模型,揭示在时间、水位、降雨等影响下,岸坡内部位移、渗压变化规律,预测岸坡位移、渗压变化趋势,利用Visual Basic语言编程实现了模型的计算。研究表明,BP神经网络模型和GM(1,1)模型均能较好的拟合及预测岸坡位移、渗压变化趋势。基于Visual Studio平台,构建可视化模块,通过TIN模型及栅格模型的导入,实现了岸坡监测可视化显示及测量、属性查询等相关功能;构建数据管理与分析模块,通过与监测数据库及外部监控模型程序建立连接,实现了监测数据管理及对监测数据的实时分析预测。和悦洲临江岸坡监测信息系统开发实例表明,该系统实现了岸坡安全监测的信息化、可视化及系统化,为岸坡加固及运行采取及时有效的防范措施提供条件。
[Abstract]:Bank slope management has played a great role in flood control, irrigation, water supply, shipping, soil and water conservation, economic and environmental benefits, national economic construction and social security. Slope safety monitoring, based on the analysis and processing of time series data produced by monitoring instruments, reveals the working state of bank slope and ensures its safe operation, which plays an important role in bank slope management. In general, in order to fully understand the running state of the bank slope, more monitoring points and monitoring items are arranged on the bank slope, and the spatial distribution of the monitoring points is also relatively wide, which constitutes a complex spatial monitoring system and produces a large number of monitoring data. Based on the above problems, this paper studies and develops the slope safety monitoring information system, and realizes the systematic management of bank slope safety monitoring. Based on GIS platform, the visualization models of riverside bank slope were established by using TIN surface and grid surface, respectively. The grid surface was textured by 3D modeling software Sketchup to make it more intuitionistic. The bank slope monitoring database is constructed to manage rainfall, displacement, osmotic pressure and other monitoring information effectively. Based on the monitoring data, the BP neural network model and the GM (1 ~ 1) model are constructed to reveal the internal displacement and seepage pressure variation law of bank slope under the influence of time, water level and rainfall, and to predict the slope displacement and seepage pressure change trend. The calculation of the model is realized by programming with Visual Basic language. The results show that both the BP neural network model and the GM (1 ~ 1) model can fit and predict the slope displacement and seepage pressure. Based on the Visual Studio platform, the visualization module is constructed. Through the introduction of the TIN model and the grid model, the related functions of bank slope monitoring, visual display and measurement, attribute query and so on are realized. The module of data management and analysis is constructed, and the monitoring data management and the real-time analysis and prediction of monitoring data are realized by establishing the connection with the monitoring database and the external monitoring model program. The example shows that the system can realize the informationization, visualization and systematization of bank slope safety monitoring, which provides the condition for bank slope reinforcement and operation to take timely and effective preventive measures.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TV698.1

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