Detecting Bursts in Water Distribution System via Penalized Functional Decomposition
Detecting Bursts in Water Distribution System via Penalized Functional Decomposition
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DOI：
10.1109/ieem45057.2020.9309770
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发表时间：
2020-12
期刊：
影响因子：
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通讯作者：
Yinwei Zhang;K. Lansey;Jian Liu
中科院分区：
文献类型：
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作者：
Yinwei Zhang;K. Lansey;Jian Liu
检测供水系统的突发情况（作为正常日常使用的异常情况）对于城市基础设施维护至关重要。基于传统统计过程控制的现有方法无法准确估计突发强度和启动时间。这项研究结合了水流数据流的功能基础扩展和惩罚分解，以参数化和估计正常用水量曲线，并检测相对较小幅度的翼梁爆裂。高保真模拟案例研究证明了所提出方法的有效性。
Detecting bursts in water distribution systems, as anomalies from normal daily usage, is of critical importance for urban infrastructure maintenance. Existing methods based on conventional statistical process control fall short of accurate estimations of burst magnitude and starting time. This research combines a functional basis expansion of water flow data stream and a penalized decomposition to parameterize and estimate the normal water usage profile and detect spars burst with a comparatively small magnitude. The effectiveness of the proposed method is demonstrated by a high-fidelity simulation case study.