Please wait a minute...
大学物理实验, 2023, 36(6): 93-97     https://doi.org/10.14139/j.cnki.cn22-1228.2023.06.018
  本期目录 | 过刊浏览 | 高级检索 |
基于BP神经网络的DMA漏损定位仿真实验设计
郑嘉龙,杨 鸽
四川水利职业技术学院 电力工程学院,四川 崇州 611231
Simulation Experiment Design of DMA LeakageLocalization Based on BP Neural Network
ZHENG Jialong,YANG Ge

下载:  PDF (1858KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 

独立计量区(District etered area,DMA)技术和漏损控制是供水企业降低供水管网运营成本的重要手段。DMA 分区优化技术在一定程度上精简了传感器配置数量,DMA 极端简单配置传感器数量条件下的漏损定位方法研究还比较鲜见。同时,现有研究成果对漏损定位方法干扰因素问题的分析还不多见。因此,基于仿真实验对漏损定位的上述两个问题进行研究。首先,介绍供水管网漏损的概念以及 DMA 技术在供水管网中的应用。然后,基于 EPANET-Matlab-Toolkit-2.1.1 包含的 Netl.inp 文件,在EPANET 仿真软件平台上采用单一人口节点配置水压和水流传感器模拟有限资源条件下的独立计量区。接着,运行 EPANET 仿真软件分别模拟理想条件情形和某供水节点需水量临时大增情形独立计量区24小时供水情况,获取两个人口节点数据集。最后采用 MATLAB 平台编写 BP 神经网络预测模型程序,并采用上述两个数据集分别进行训练测试。结果显示理想条件下 BP 神经网络预测模型在有限资源条件下的 DMA 浦损定位精度很高,供水节点需水量临时大增情形将增大模型预测误差。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
郑嘉龙
杨 鸽
关键词:  漏损定位  独立计量区  BP神经网络  EPANET仿真  MATLAB 仿真     
Abstract: 

District metered area( DMA) technology and leakage control are important means for water supplyenterprises to reduce the operating costs of water supply networks.DMA partition optimization technology has tosome extent simplified the number of sensor configurations , but research on leak localization methods underextremely simple sensor configuration conditions in DMA is still relatively rare.At the same time , the existingresearch results are rare in the analysis of Confounding of leakage location methods. Therefore , based onsimulation experiments the above two issues of leakage localization are studied. Firstly ,introduce the concept ofwater supply network leakage and the application of DMA technology in water supply networks.Then ,based onthe Netl.inp file included in EPANET Matlab Toolkit 2.1.1,a single inlet node was used to configure waterpressure and flow sensors on the EPANET simulation software platform to simulate independent metering zonesunder limited resource conditions.Next ,run EPANET simulation software to simulate the 24-hour water supplsituation in the independent metering area under ideal conditions and a temporary increase in water demand ata certain water supply node ,and obtain two datasets for the inlet nodes.Finally,a BP neural network predictionmodel program was developed using the MATLAB platform, and the two datasets were trained and tested separately. The results show that under ideal conditions, the BP neural network prediction model has highaccuracy in DMA leakage localization under limited resource conditions ,and the temporary increase in water demand at water supply nodes will increase the model prediction error.

Key words:  leakage localization    DMA    BP neural network    EPANET simulation    MATLAB simulation
                    发布日期:  2023-12-25     
ZTFLH:  TU 991  
引用本文:    
郑嘉龙, 杨 鸽. 基于BP神经网络的DMA漏损定位仿真实验设计 [J]. 大学物理实验, 2023, 36(6): 93-97.
ZHENG Jialong, YANG Ge. Simulation Experiment Design of DMA LeakageLocalization Based on BP Neural Network . Physical Experiment of College, 2023, 36(6): 93-97.
链接本文:  
http://dawushiyan.jlict.edu.cn/CN/10.14139/j.cnki.cn22-1228.2023.06.018  或          http://dawushiyan.jlict.edu.cn/CN/Y2023/V36/I6/93
No related articles found!
[1] . [J]. Physical Experiment of College, 2020, 33(1): 0 .
[2] . [J]. Physical Experiment of College, 2020, 33(1): 0 .
[3] WU Ming, ZENG Hong, ZHANG Wenpeng, ZHANG Yuanwei, DAI Zhenbing. Theoretical and Experimental Research of A zimuthal-Radial Pendulum [J]. Physical Experiment of College, 2020, 33(1): 1 -6 .
[4] LIU Weiwei, SUN Qing, LIU Chenglin. Research on Selection of Critical Magnetization Current for Measuring Charge-Mass Ratio of Electron by Magnetron Controlling [J]. Physical Experiment of College, 2020, 33(1): 7 -9 .
[5] DENG Li, LIU Yang, ZHANG Hangzhong, ZHOU Kewei, ZHAO guoru, WEI luanyi. MATLAB simulation of Fourier transform of Gaussian beam and the spatial filtering effects basing on 4F optical imaging system [J]. Physical Experiment of College, 2020, 33(1): 10 -16 .
[6] MA Kun. Experiment Study on the Measuring Young' s Modulus by Stretching [J]. Physical Experiment of College, 2020, 33(1): 17 -20 .
[7] FEI Xianxiang, CHEN Chunlei, WANG Wenhua, SHI Wenqing, HUANG Cunyou. Design of Lens Group Focal Length Measurement System Based on Object-Image Parallax Comparison [J]. Physical Experiment of College, 2020, 33(1): 21 -24 .
[8] LI Chunjiang, LI Luyu, YANG Jinglei, LI Tingrong, XIANG Wenli. A New Method for Simple and Rapid Measurement of Refractive Index [J]. Physical Experiment of College, 2020, 33(1): 25 -28 .
[9] WANG Cuiping, YAO Mengyu, YE Liu, LI Aixia, ZHANG Ziyun, DAI Peng. Progress and Applications of Electron Spin Resonance in Biology [J]. Physical Experiment of College, 2020, 33(1): 29 -33 .
[10] CHEN Yingmo, SHEN Siyi, WANG Jie. Study on the Characteristics of Silicon Photocells [J]. Physical Experiment of College, 2020, 33(1): 34 -36 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed