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Prognosis of quality sensors in the Barcelona drinking water network

机译：巴塞罗那饮用水网络中质量传感器的预后

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摘要

One of the most important areas of the water utilities is the water quality management. This area is responsible of guaranteeing safety in the water supply to the citizens. The strategy to guarantee the safety is based on two principal elements: disinfection and monitoring. Disinfection techniques, such as chlorination, allow to prevent the growing of microorganisms present in the water. Moreover, in order to guarantee this safety in the whole water network and avoid any unexpected event, on-line sensors are required to monitor a set of quality parameters. The whole process is based on the assumption that the information retrieved from quality sensors is totally reliable. But due to the complexity of the calibration and maintenance of these chemical sensors, several factors affect the accuracy of the raw data collected. Consequently, any decision based on this raw data might be based on a non solid base. Therefore, this work presents a data analytics approach consisting in two modules: fault diagnosis and prognosis. The fault diagnosis module first discerns if a sensor is detecting a real change on water quality parameters or actually is providing inconsistent information due to some malfunction. The prognosis module aims to predict the fault instant due to a slow degradation, which is very common in chlorine sensors. This approach allows to apply a predictive maintenance strategy reducing corrective actions. The proposed methodology has been satisfactorily tested on the Barcelona Drinking Water Network.
机译：水务部门最重要的领域之一是水质管理。该地区负责确保向市民供水的安全。保证安全的策略基于两个主要要素：消毒和监控。诸如氯化的消毒技术可以防止水中微生物的生长。此外，为了确保整个水网的安全并避免任何意外事件，需要使用在线传感器来监视一组质量参数。整个过程基于以下假设：从质量传感器检索到的信息是完全可靠的。但是由于这些化学传感器的校准和维护很复杂，因此有几个因素会影响所收集原始数据的准确性。因此，基于此原始数据的任何决策都可能基于非可靠的基础。因此，这项工作提出了一种由两个模块组成的数据分析方法：故障诊断和预后。故障诊断模块首先识别传感器是否正在检测水质参数的实际变化或由于某些故障而实际上提供的信息不一致。预后模块旨在预测由于缓慢降解而引起的故障瞬间，这在氯传感器中非常常见。这种方法允许应用减少维护措施的预测性维护策略。所提议的方法已在巴塞罗那饮用水网络上得到令人满意的测试。

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