A Robust Multi-Objective Pressure Sensor Placement Method for Burst Detection in Water Distribution Systems
Kun Du (Kunming University of Science and Technology)
Jinxin Yu (Kunming University of Science and Technology)
Feifei Zheng (Kunming University of Science and Technology, Zhejiang University)
Wei Xu (Kunming University of Science and Technology)
Dragan Savic (University of Exeter, KWR Water Research Institute)
Z. Kapelan (TU Delft - Sanitary Engineering)
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Abstract
Bursts in water distribution systems (WDSs) lead to water wastage and negative environmental impacts. Optimizing pressure sensor placement (PSP) for effective burst detection is crucial for prompt response and adverse event mitigation. While many optimization methods are available for this purpose, their resulting PSP strategies often exhibit large variability caused by background noise or metering accuracy, representing low robustness. This consequently hinders the wide application of existing PSP methods for burst detection in WDSs. This study proposes a novel multi-objective PSP method aimed at maximizing burst detection while minimizing the number of sensors. Within this method, a new threshold metric is introduced to quantify the minimum detectable burst outflow across all pipes. The metric has the key advantage of taking into account the fact that the relative magnitude of the detectable threshold for different pipes is independent of noise, thereby addressing the low robustness issue. The proposed method is applied to three WDSs, and results show that it can consistently achieve robust optimal PSP strategies across diverse noise conditions. Comprehensive comparisons between the proposed method and the other benchmark approaches are conducted using five metrics, including detection performance and layout characteristics. These comparisons reveal the properties of each optimization method and show how detection performance is affected by various placement features. It is anticipated that the proposed method can be useful in engineering practice due to its great robustness in determining the optimal PSP strategies for burst detection in WDSs compared to other alternatives.