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Network hydraulics inclusion in water quality event detection using multiple sensor stations data

机译:使用多个传感器站数据将网络液压纳入水质事件检测中

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Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. (C) 2015 Elsevier Ltd. All rights reserved.
机译:事件检测是水分配系统分析中当前最具挑战性的主题之一:如何有效地在不同的网络位置进行常规的在线液压(例如压力,流量)和水质(例如pH值,残留氯,浊度)测量用于检测水质污染事件。这项研究描述了一个集成的事件检测模型,该模型将多个传感器站数据与网络液压系统相结合。迄今为止,事件检测建模可能仅限于单个传感器站的位置和数据集。单传感器站模型与网络液压系统的见解脱节,因此可能会明显受到误报。这项工作旨在通过将局部和空间水力数据理解集成到事件检测模型中来减少这种限制。空间分析通过探索传感器相互的液压影响,通过发现特征较低的事件来补充本地事件检测工作。这项研究的独特贡献在于将水力模拟信息纳入空间分布传感器的整体事件检测过程。该方法论在两个使用基础试验和灵敏度分析的示例应用中得到了证明。结果表明,与单传感器事件检测方案相比,建议的模型具有明显的优势。 (C)2015 Elsevier Ltd.保留所有权利。

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