Premium
Multi‐Sensor Fusion for Transient‐Based Pipeline Leak Localization in the Dempster‐Shafer Evidence Framework
Author(s) -
Lin Jingrong,
Wang Xun,
Ghidaoui Mohamed S.
Publication year - 2021
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2021wr029926
Subject(s) - leak , leakage (economics) , leak detection , dempster–shafer theory , sensor fusion , computer science , transient (computer programming) , signature (topology) , artificial intelligence , noise (video) , pipeline (software) , data mining , pattern recognition (psychology) , real time computing , electronic engineering , engineering , mathematics , economics , image (mathematics) , macroeconomics , programming language , operating system , geometry , environmental engineering
Abstract Detecting a small leak in a water‐supply pipe with a wave scattering power of the order of noise or smaller is a challenging problem because its signature in a measured signal is weak. Experimental data show that multiple sensors enhance the evidence about a leak in a transient test and, thus, increase the possibility of successful leak detection in noisy environments. Therefore, a leakage localization scheme is proposed, which fuses multi‐sensor measurements in the Dempster‐Shafer evidence framework. The signature of a leak in each measurement is extracted and translated into a piece of evidence regarding its presence and location. Then, the pieces of evidence from different sensors are fused using the Dempster's rule of combination to form a unified leak location estimation. The proposed method is model‐free and is thus insensitive to imprecise knowledge of pipe system. The gain of the multi‐sensor fusion mechanism on the leakage localization accuracy is demonstrated via both numerical and experimental data.