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首页> 外文期刊>Journal of Hydroinformatics >A method for quantitative discrimination in flow pattern evolution of water distribution supply areas with interpretation in terms of demand and leakage
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A method for quantitative discrimination in flow pattern evolution of water distribution supply areas with interpretation in terms of demand and leakage

机译:配水区流态演化定量判别的方法

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摘要

A method, the comparison of flow pattern distributions (CFPD), is described in which the specific representation of flow measurements for two different time periods allows a direct, quantitative interpretation of changes in the pattern. Two types of changes can be distinguished. The first is changes from one period to the next in demand consistent with the existing pattern, e.g. due to changing weather or changes in the population size. The second type is inconsistent changes which may be due to increased leakage. The method is successfully applied to drinking water distribution systems of different sizes and characteristics. Being data driven, it is independent of model assumptions and therefore insensitive to uncertainties therein which may hinder some other leakage determination methods. Because it is simple to implement and apply but nevertheless powerful in distinguishing between consistent and inconsistent changes in water demand, the method provides water companies with a way to constantly monitor their networks for possible changes in customer demand and the possible occurrence of new leakages and also check archived data for similar changes. This could render additional information about customer behavior and the evolving condition of the network from data which is usually readily available at water companies.
机译:描述了一种比较流型分布(CFPD)的方法,其中针对两个不同时间段的流量测量值的特定表示可以对模式的变化进行直接,定量的解释。可以区分两种类型的更改。第一个是与现有模式一致的需求从一个时期到下一个时期的变化,例如由于天气变化或人口规模的变化。第二类是不一致的变化,可能是由于泄漏增加所致。该方法成功地应用于不同大小和特征的饮用水分配系统。由于是数据驱动的,因此它与模型假设无关,因此对其中的不确定性不敏感,这可能会妨碍其他某些泄漏确定方法。由于易于实施和应用,但是在区分需求的一致和不一致变化时仍然很有效,因此该方法为自来水公司提供了一种方法,可以不断监控其网络,以了解客户需求的可能变化以及是否可能发生新的泄漏,以及检查存档数据是否有类似更改。这可以从供水公司通常容易获得的数据中提供有关客户行为和网络发展状况的其他信息。

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