Abstract: 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 several 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.

Key words: secondary water distribution networks, leakage location, K-means clustering algorithm, pressure data, data driven