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Pump Efficiency Analysis of Waste Water Treatment Plants: A Data Mining Approach Using Signal Decomposition for Decision Making

机译:废水处理厂的泵效率分析:一种利用信号分解解决决策的数据挖掘方法

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In Waste Water Treatment Plants (WWTPs), the pump systems are one of the most energy intensive processes. An efficient energy management of pumps should produce environmental and economic benefits. In this paper, we propose a daily data-driven approach for a detailed pump efficiency analysis that reduces the time gap between an inefficiency and its detection, provides detailed information for decision making by using new Key Performance Indicators (KPIs), and detects inefficient pump set-ups and designs. The proposed approach based on signal decomposition relies on sensors generally available in WWTPs, e.g. daily pump inflow and energy consumption. Moreover, it allows decomposing the data signal in an automatic way into a long-term trend and short-term fluctuations. This information can then be used to support plant managers more effectively.
机译:在废水处理厂(WWTPS)中,泵系统是最能量的密集过程之一。泵的有效能量管理应产生环境和经济效益。在本文中,我们提出了一种日常数据驱动方法,用于详细的泵效率分析,减少低效率与其检测之间的时间间隙,提供了使用新的关键性能指标(KPI)来决策的详细信息,并检测效率泵设置和设计。基于信号分解的所提出的方法依赖于WWTPS通常可用的传感器,例如,每日泵流入和能耗。此外,它允许以自动方式将数据信号分解成长期趋势和短期波动。然后可以使用这些信息更有效地支持工厂管理者。

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