东濠涌深隧排水系统内涝监测与控制优化研究
发布时间：2018-08-30 12:14
【摘要】：每逢遇到强降雨,广州容易出现内涝,对城市交通和居民生活造成较大的影响。为解决城市内涝等方面的问题,广州正在开展东濠涌深隧排水系统试验段工程建设和研究。由于深隧排水系统构成复杂,管理难度大,我国大陆又无此类工程可参考,因此需进一步探索高效、合理的深隧排水系统的调度运行方式。本文通过综述国外深隧排水系统运行方式及我国城市排水和深隧建设情况,根据广州东濠涌流域的排水系统现状及现行调度运行方式,采用实际调研、理论分析研究、数学方法等理论与实际相结合的研究方法,进行东濠涌深隧排水系统内涝监测与控制优化研究,主要研究成果如下:结合内涝点现场调研以及内涝统计数据、排水管网图等资料,分析东濠涌流域2010年-2014年36个内涝点情况,最终在东濠涌深隧排水系统上游的浅层排水管网增加选取12个内涝点监测点。所选内涝监测点能较好反映流域的内涝情况,并均能通过深隧排水系统和浅层排水管网闸泵站进行内涝控制,为实现东濠涌排水系统内涝监测与控制优化提供必要的基础条件。围绕如何实现对内涝点液位的实时监测与预警,针对内涝点环境特点和目前仅监测路面积水的不足,基于给水排水、物联网和自动化控制等专业技术,设计构建一套内涝液位监测系统。经测试运行,系统能有效实现内涝点液位、设备工况等数据信息采集与无线远程传输,液位信息在线查询以及历史数据调用,实现对东濠涌深隧排水系统内涝监测优化,并为深隧排水系统内涝控制优化研究提供实时、准确的数据基础。基于东濠涌流域[V渔岗片区内涝监测点的实测液位数据,进行液位变化规律分析,并利用BP神经网络建立东濠涌流域[V渔岗片区的内涝点与深隧排水系统、浅层排水系统闸站的液位变化关系模型。经模型计算结果分析,东濠涌深隧东风路竖井的开闸液位从7.50m(城建标高)提高至8.38m(城建标高),并可优先利用浅层闸站进行内涝控制。经优化后,可以减少深隧排水系统的使用次数,降低深隧排水系统的运行维护成本,为探索高效、合理的深隧排水系统调度运行提供一种科学有效的方法。
[Abstract]:Whenever there is heavy rainfall, Guangzhou is prone to waterlogging, which has a great impact on urban traffic and residents' life. In order to solve the problems of urban waterlogging, Guangzhou is carrying out the construction and research of the test section of the Haozhou deep tunnel drainage system in Tung Chung. Because the structure of deep tunnel drainage system is complex and the management is difficult, and there is no such project in mainland China, it is necessary to further explore the efficient and reasonable dispatching and operation mode of deep tunnel drainage system. This paper summarizes the operation mode of deep tunnel drainage system in foreign countries and the situation of urban drainage and deep tunnel construction in our country. According to the present situation of drainage system and current dispatching operation mode of Donghao River Basin in Guangzhou, this paper adopts practical investigation and theoretical analysis and research. The main research results are as follows: combined with the field investigation of the waterlogging point and the statistical data of the waterlogging, the main research results are as follows: based on the combination of mathematical methods and practical research methods, the waterlogging monitoring and control optimization of the Tonghong Haohao deep tunnel drainage system is carried out. Based on the data of drainage network diagram and other data, the situation of 36 waterlogging points in Donghao River Basin from 2010 to 2014 is analyzed. Finally, 12 monitoring points are added to the shallow drainage pipe network in the upper reaches of Donghao deep tunnel drainage system. The selected waterlogging monitoring points can better reflect the waterlogging situation of the basin, and can be controlled by deep tunnel drainage system and shallow drainage pipe network sluice pump station, which provides the necessary basic conditions for the waterlogging monitoring and control optimization of Donghao drainage system. Focusing on how to realize the real-time monitoring and warning of the water level in the waterlogging point, aiming at the environmental characteristics of the waterlogging point and the shortage of only monitoring the surface water at present, the paper bases on the professional technologies such as water supply and drainage, Internet of things and automation control, etc. Design and build a set of waterlogging level monitoring system. After testing and running, the system can effectively realize the collection and wireless remote transmission of the water level of the waterlogging point, the working condition of the equipment, the on-line query of the liquid level information and the transfer of historical data, so as to realize the optimization of the waterlogging monitoring and optimization of the Donghao deep tunnel drainage system. It also provides real-time and accurate data base for waterlogging control optimization of deep tunnel drainage system. Based on the measured liquid level data of waterlogging monitoring points in Donghao River Basin, the variation law of water level is analyzed, and the waterlogging point and deep tunnel drainage system in Donghao River Basin [V Yugang area] are established by using BP neural network. Model of liquid level variation in sluice station of shallow drainage system. The results of the model analysis show that the opening liquid level of the Dongfeng shaft in Dongfeng deep tunnel is increased from 7.50m to 8.38m, and the shallow sluice station can be used for waterlogging control. After optimization, the operation and maintenance cost of deep tunnel drainage system can be reduced, which provides a scientific and effective method for exploring efficient and reasonable operation of deep tunnel drainage system.
【学位授予单位】：广州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU992
本文编号：2213040
[Abstract]:Whenever there is heavy rainfall, Guangzhou is prone to waterlogging, which has a great impact on urban traffic and residents' life. In order to solve the problems of urban waterlogging, Guangzhou is carrying out the construction and research of the test section of the Haozhou deep tunnel drainage system in Tung Chung. Because the structure of deep tunnel drainage system is complex and the management is difficult, and there is no such project in mainland China, it is necessary to further explore the efficient and reasonable dispatching and operation mode of deep tunnel drainage system. This paper summarizes the operation mode of deep tunnel drainage system in foreign countries and the situation of urban drainage and deep tunnel construction in our country. According to the present situation of drainage system and current dispatching operation mode of Donghao River Basin in Guangzhou, this paper adopts practical investigation and theoretical analysis and research. The main research results are as follows: combined with the field investigation of the waterlogging point and the statistical data of the waterlogging, the main research results are as follows: based on the combination of mathematical methods and practical research methods, the waterlogging monitoring and control optimization of the Tonghong Haohao deep tunnel drainage system is carried out. Based on the data of drainage network diagram and other data, the situation of 36 waterlogging points in Donghao River Basin from 2010 to 2014 is analyzed. Finally, 12 monitoring points are added to the shallow drainage pipe network in the upper reaches of Donghao deep tunnel drainage system. The selected waterlogging monitoring points can better reflect the waterlogging situation of the basin, and can be controlled by deep tunnel drainage system and shallow drainage pipe network sluice pump station, which provides the necessary basic conditions for the waterlogging monitoring and control optimization of Donghao drainage system. Focusing on how to realize the real-time monitoring and warning of the water level in the waterlogging point, aiming at the environmental characteristics of the waterlogging point and the shortage of only monitoring the surface water at present, the paper bases on the professional technologies such as water supply and drainage, Internet of things and automation control, etc. Design and build a set of waterlogging level monitoring system. After testing and running, the system can effectively realize the collection and wireless remote transmission of the water level of the waterlogging point, the working condition of the equipment, the on-line query of the liquid level information and the transfer of historical data, so as to realize the optimization of the waterlogging monitoring and optimization of the Donghao deep tunnel drainage system. It also provides real-time and accurate data base for waterlogging control optimization of deep tunnel drainage system. Based on the measured liquid level data of waterlogging monitoring points in Donghao River Basin, the variation law of water level is analyzed, and the waterlogging point and deep tunnel drainage system in Donghao River Basin [V Yugang area] are established by using BP neural network. Model of liquid level variation in sluice station of shallow drainage system. The results of the model analysis show that the opening liquid level of the Dongfeng shaft in Dongfeng deep tunnel is increased from 7.50m to 8.38m, and the shallow sluice station can be used for waterlogging control. After optimization, the operation and maintenance cost of deep tunnel drainage system can be reduced, which provides a scientific and effective method for exploring efficient and reasonable operation of deep tunnel drainage system.
【学位授予单位】：广州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU992
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