面对建筑二次供水管网的漏损问题,现阶段通常采用检漏仪器配合人工经验的技术手段进行检测.针对上述方法耗时长、效率低等问题,提出一种数据驱动的增量式建筑二次供水管网漏损定位方法.该方法通过高频采集管网中各个压力监测点数据,建立未漏损工况下建筑二次供水管网压力数据集,并采用K均值算法对数据集进行聚类,形成不同时段压力特征数据,用以判断新采集的节点压力向量是否异常,进而判定是否发生漏损,并定位漏损节点位置.实验结果表明,该方法可实现建筑二次供水管网漏损定位,较现有方法发现漏损用时短、定位速度快等优势,具有一定的实用价值.
Solving the leakage problem of the secondary water distribution networks often requires the combination of detection instruments and worker experience. However, this kind of method has severed disadvantages, such time consumption, low efficiency and strong subjectivity. A new leakage location method based on data analysis was proposed. The method gathered data from networks' pressure monitoring points at a high frequency and then built a data set under a no-leakage condition. K means clustering algorithm was used to classify the data set, thus obtaining the pressure data features in different times. Comparing the new nodal pressure vector with the data set, one can find whether there is leakage and where it is. Experimental results show that the method can help locate leakage in secondary water distribution networks. Compared with the existing methods, the proposed approach is faster and more objective and of higher practical value.