基于改进物元法及监控模型的大坝安全动态评价研究

发布时间：2018-03-09 14:30

本文选题：大坝　切入点：物元可拓理论　出处：《合肥工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：横跨河床的水库大坝是一种优化水资源配置的重要挡水建筑物,是调控水资源时间分布的一项重要工程措施。由水库大坝等建筑物组成的江河防洪工程体系在灌溉、防洪、发电等方面皆发挥了巨大的作用,正是由于在社会、经济、国民生活等等方面大坝发挥着越来越重要的作用,人们亦愈加重视大坝的安全问题。大坝的安全状况受到众多因素影响,如何充分利用大坝的监测信息,客观有效地评价大坝的安全状况是大坝安全评判中急需解决的问题。本文在物元可拓理论的基础上,针对传统物元评价模型应用中存在的局限性,对物元可拓方法进行了修正,在点与区间的距和等级评定的计算方法上进行了改进。以大坝安全监测指标数据为基础,结合大坝安全评价的特点,将改进物元可拓方法应用于大坝安全评价中,采用熵权法确定各指标的权重,通过对比度确定待评大坝的安全等级,构建出基于改进物元的大坝安全评价模型。本文选取具有重要性且监测数据相对完备的位移、上下游水位、气温为评价指标,结合大坝安全评价的改进物元模型,对大坝安全做出评价,并通过分析比较多种关联函数的计算结果,得出合理的适合实际工程应用的关联函数。实例分析结果验证了本文改进模型的合理有效性,能客观反映大坝安全的实际状态,为大坝安全综合评价提供了一种科学、有效的分析手段。在大坝的实际运行中,随着时间的推移大坝的安全状态也随之发生变化,因此不仅需要掌握大坝的安全现状,还需要了解大坝未来一定时段内的状态,基于此,本文采用BP神经网络预测模型建立了大坝位移与水压、气温及时效因素之间的预测模型,并对大坝位移做出预测。在大坝的位移指标预测数据的基础上,结合大坝安全评价的改进物元模型,实现对大坝安全的预评价。待已经获得后期的位移实测值后,进而采用动态等维新息思想,结合BP神经网络预测模型及改进的物元评价模型,实现对大坝的动态综合评价。
[Abstract]:The reservoir dam across the river bed is an important water retaining structure for optimizing the allocation of water resources and an important engineering measure for regulating the time distribution of water resources. Power generation has played a huge role, precisely because the dam is playing an increasingly important role in social, economic, national life, etc. People also pay more and more attention to the safety of dams. The safety of dams is affected by many factors. How to make full use of the monitoring information of dams, The objective and effective evaluation of dam safety is an urgent problem in dam safety evaluation. Based on the matter-element extension theory and the limitation of traditional matter-element evaluation model, the matter-element extension method is modified. Based on the dam safety monitoring index data and the characteristics of dam safety evaluation, the improved matter-element extension method is applied to dam safety evaluation. The weight of each index is determined by using entropy weight method, and the safety grade of dam to be evaluated is determined by contrast, and a dam safety evaluation model based on improved matter-element is constructed. In this paper, the displacements, which are important and the monitoring data are relatively complete, are selected. The upstream and downstream water level and air temperature are used as evaluation indexes, and combined with the improved matter-element model of dam safety evaluation, the dam safety is evaluated, and the calculation results of various correlation functions are analyzed and compared. A reasonable correlation function suitable for practical engineering application is obtained. The result of case analysis verifies the reasonable validity of the improved model, which can objectively reflect the actual state of dam safety and provide a scientific method for the comprehensive evaluation of dam safety. Effective means of analysis. In the actual operation of the dam, the safety state of the dam changes with the passage of time, so it is necessary not only to master the present safety situation of the dam, but also to understand the state of the dam in a certain period of time in the future. Based on this, the prediction model of dam displacement and water pressure, air temperature and time-dependent factors is established by using BP neural network prediction model, and the dam displacement is forecasted on the basis of the prediction data of dam displacement index. Combined with the improved matter-element model of dam safety evaluation, the pre-evaluation of dam safety is realized. Combined with BP neural network prediction model and improved matter-element evaluation model, the dynamic comprehensive evaluation of dam can be realized.
【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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