供水管网重大漏损事故模拟、定位与控制技术
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摘要
城市供水系统具有规模大、分布范围广、隐蔽性强的特点,在供水管网发生重大漏损事故时往往不易及时发现,给人民的生命安全和社会财富带来严重的隐患。供水管网重大事故的识别及定位技术一直是困扰供水行业的难题,目前国内外很多科研机构和企业都在开展相关技术研究,但都存在投资大、精度低,还处于理论研究阶段,难以直接投入到实际应用中。
     本论文首先介绍了供水管网动态管理GIS技术、管网建模技术和SCADA技术,分别介绍了各种技术的概念、方法、建立过程以及在管网事故中的应用,并结合实例进行分析,这些技术为管网事故定位奠定基础。
     本论文第三章详细论述了供水管网事故时的压力突变特征,并在供水管网突发重大漏损事故情况下对管网运行状态进行仿真模拟:通过建立管网微观水力模型,进行突发重大事故时的计算机仿真模拟,评估爆管造成的管网监测点压力的变化,并通过实例分析,建立供水管网漏损事故特征信息库。
     本论文第四章重点论述了事故区的判别、事故点的定位技术,提出了“二步法”准确定位事故点的方法:第一步基于BP神经网络法智能识别事故区域,首先用漏损事故特征信息库对BP神经网络进行学习与训练,建立事故区与监测点压力变化之间的非线性关系,然后将各监测点压力的变化作为已知条件利用该神经网络来预测事故区的位置。第二步是在第一步的基础上,基于微观水力模型技术用统计学方法实现可疑事故点的定位,并用黄金分割法实现了漏损水量的估算。
     本论文最后探讨了供水管网漏损事故控制的几种关键技术,即分区管理、压力管理和管网安全评估模型,系统的介绍了这几种技术的工作原理、建设原则和思路流程,提出了基于统计学分析和基于事故树分析的方法对管网进行安全评估,并结合某特区进行了管网漏损的控制策略与实践研究。
Urban water supply system has the characteristics of large-scale, wide distribution and concealment. It is often difficult to detect the major leakage accident when it happens in water supply network. So it brings serious risks for people lives and social wealth. Water supply industry has been troubled by techniques of identifying and locating the major accidents for a long time. Many research institutions and companies are conducting research on related technologies. But because of large investment and low precision, the study is still on the stage of theoretical research, and it is difficult to be used directly into practical applications.
     Techniques of GIS, SCADA and Simulation for dynamic management of water supply network have been introduced at the beginning of the paper. Concept methods, establishing process and application on network accident with examples have been introduced. These kinds of technique lay the foundation for locating the major accident.
     In the third chapter, characteristic of pressure changes under the circumstances in emergencies has been analyzed in detail. And hydraulic model has been setup in this case. Using detail model, assessment has been done for the pressure changes at all the SCADA pressure points due to pipe burst. Through the example analysis, characteristic information database for major leakage accident in water supply network has been established.
     In the fourth chapter, analysis has been focused on discrimination of the accident, the accident point positioning technology, and two-step method of accurately positioning the accident points has been proposed. First step is to use BP neural network intelligent to recognize accident area. At the beginning, the leakage accident characteristic database has been used to do the learning and training for BP neural network, and establish the nonlinear relationship between accident area and pressure variation at SCADA pressure points. And then use the pressure change at SCADA points as known conditions to predict the location of the accident area. Second step is to use the detail hydraulic model to identify the suspicious accident points by statistical method. And also leakage volume has been calculated by golden section method.
     In the last section of the paper, several critical techniques of water supply system leakage accident control have been discussed, like DMA, pressure management and network risk evaluation model. Theories, principles and process have been presented, and risk evaluation based on statistical analysis and fault tree analysis methods have been proposed. Through the active preventive measures, frequency of major accidents will be reduced. At last, leakage control strategy and practice are discussed according to the actual water supply network of one city.
引文
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