...
首页> 外文期刊>Procedia - Social and Behavioral Sciences >Improving Analytics in Urban Water Management: A Spectral Clustering-based Approach for Leakage Localization
【24h】

Improving Analytics in Urban Water Management: A Spectral Clustering-based Approach for Leakage Localization

机译:改善城市水管理中的分析:基于谱聚类的泄漏局部化方法

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Worldwide growing water demand has been forcing utilities to successfully manage their costs. Contemporarily, within an era of tight budgets in most economic and social sectors, it affects also Water Distribution Networks (WDN). So, an efficient urban water management is needed to get a balance between consumer satisfaction and infrastructural assets inherent to WDN. Particular case is referred to pipe networks which suffer for frequent leaks, failures and service disruptions. The ensuing costs due to inspection, repair and replacement, are a significant part of operational expenses and give rise to difficult decision making. Recently, the goal regarding the improvement of the traditional leakage management process through the development of analytical leakage localization tools has been brought to the forefront leading to the proposal of several approaches. The basis of all methods relies on the fact that leaks can be detected correlating changes in flow to the output of a simulation model whose parameters are related to both location and severity of the leak. This paper, starting from a previous work of the authors, shows how the critical phases of leak localization can be accomplished through a combination of hydraulic simulation and clustering. The research deals with the benefits provided by Spectral Clustering which is usually adopted for network analysis tasks (e.g., community or sub-network discovery). A transformation from a data points dataset, consisting of leakage scenarios simulated through a hydraulic simulation model, to a similarity graph is presented. Spectral Clustering is then applied on the similarity graph and results are compared with those provided by traditional clustering techniques on the original data points dataset. The proposed spectral approach proved to be more effective with respect to traditional clustering, having a better performance to analytically localize leaks in a water distribution network and, consequently, reducing costs for intervention, inspection and rehabilitation.
机译:全球不断增长的用水需求迫使公用事业公司成功地管理其成本。同时,在大多数经济和社会领域预算紧缩的时代,它也影响了供水网络(WDN)。因此,需要有效的城市用水管理,以在消费者满意度和WDN固有的基础设施资产之间取得平衡。特别是涉及经常发生泄漏,故障和服务中断的管道网络。由于检查,维修和更换而产生的后续费用是运营费用的重要组成部分,并且会导致决策困难。最近,关于通过开发分析性泄漏定位工具来改进传统泄漏管理流程的目标已被带到了最前沿,从而提出了几种方法。所有方法的基础都依赖于以下事实:可以检测泄漏,将流量变化与模拟模型的输出相关联,该模拟模型的参数与泄漏的位置和严重性有关。本文从作者先前的工作开始,展示了如何通过水力模拟和聚类相结合来完成泄漏定位的关键阶段。该研究涉及频谱聚类提供的好处,频谱聚类通常用于网络分析任务(例如,社区或子网发现)。提出了从数据点数据集到相似度图的转换,该数据点数据集包含通过水力模拟模型模拟的泄漏情景。然后将光谱聚类应用于相似度图,并将结果与​​传统聚类技术在原始数据点数据集上提供的结果进行比较。事实证明,所提出的频谱方法相对于传统群集更为有效,具有更好的性能来分析水分配网络中的泄漏,从而降低了干预,检查和修复的成本。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号