Optimization Layout Method of Pressure Monitoring Points in Water Supply Network Based on Density Peak Improved Partitioning Around Medoids Algorithm

In recent years, with the continuous expansion of the water supply network scale, leakage problems have also occurred frequently, so the leakage monitoring of urban water supply networks has received increasing attention. How to scientifically and reasonably arrange pressure monitoring points in the water supply network is the key to real-time and effective monitoring of leakage. In response to this issue, this article proposes an optimized layout method for pressure monitoring points in water supply networks based on density peak improved Partitioning Around Medoids (PAM) algorithm. Firstly, by obtaining the spatial attributes of the nodes in the water supply network, the sensitivity of the nodes is calculated, and the node feature matrix data is constructed. Then, use the density peak algorithm to determine the initial clustering center of the PAM algorithm. Finally, the algorithm is used to cluster the node feature matrix data and determine the location and number of pressure monitoring points within the urban water supply network monitoring area. The experimental results show that compared with the traditional PAM algorithm, this algorithm effectively solves the problem of poor result stability caused by the randomness of the initial clustering center, and significantly improves stability and coverage node rate. The improved PAM algorithm achieves a coverage node rate of 97.76% for the layout plan of pressure monitoring points, effectively ensuring that pressure monitoring points can comprehensively and reasonably grasp the hydraulic information of the entire urban water supply network, which has guiding significance for the leakage monitoring of urban water supply networks.