Near Real-time Leak Location by Inverse Analysis Integrating Measurement Uncertainty
Bruno Ferreira, Nelson Carriço, Dídia Covas
Abstract
Abstract This paper presents a novel model-based method for near real-time pipe burst location in water distribution networks by integrating measurement uncertainty into inverse analysis. The method accounts for expected errors between measured and computed values, providing a pipe burst location area whose size varies according to the expected error level and the burst size. The proposed method is demonstrated and compared with the traditional inverse approach using a real case study with artificial bursts of different sizes and with different pressure signal noise levels. The performance of both methods is also assessed and discussed considering the effect of seasonal water demands. The traditional inverse analysis fails to accurately locate the pipe burst events, and depending on the expected error level and pipe burst size, the obtained locations may be significantly further away from the real burst location. Conversely, the proposed method does not point to the exact burst location but provides an approximated area in which step-testing can be carried out to pinpoint the exact burst location; the size of this area can be larger or smaller depending on the burst flow rate and signal uncertainty.