Leakage Detection in Water Distribution Networks Based on Semi-fixed-length Sliding Window
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摘要:
精准检测漏损是降低供水管网漏损率的关键,本文提出基于半定长滑动窗口数据的漏损检测方法.该方法采用半定长滑动窗口检测管网漏损时序流量数据,以长度递增且最大长度受限的动态窗口提升获取数据的信息质量;基于CFSFDP(Clustering by Fast Search and Find of Density Peaks)快速聚类算法,在漏损数据识别过程中,依据数据分布特性引入熵函数实现截断距离参数的自适应选择,以提高漏损事件的检出率.实验结果表明本文算法能有效地检测出供水管网四个模拟场景的漏损事件,并获得较高漏损检出率与较低的误报率.
Abstract:
Accurate detection of leakage is the key to reduce the leakage rate of water distribution networks. This paper proposes a leakage detection method based on a semi-fixed-length sliding window. The method uses a sliding window to detect leakages by analyzing the time series flow data and improves the information quality of the acquired data with a variable-length window, in which the length of the window is limited. Based on Clustering by Fast Search and Find of Density Peaks(CFSFDP),the entropy function is introduced to adaptively select cutoff distance parameters according to the data distribution characteristics. In this way, the detection rate of leakage events is improved. The experimental results show that the proposed algorithm can effectively detect the leakage data in the four simulated scenarios, and obtain a higher leakage detection rate and a lower false alarm rate.