Benchmarking dataset for leak detection and localization in water distribution systems

Autor: Mohsen Aghashahi, Lina Sela, M. Katherine Banks
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Data in Brief, Vol 48, Iss , Pp 109148- (2023)
Druh dokumentu: article
ISSN: 2352-3409
DOI: 10.1016/j.dib.2023.109148
Popis: This paper presents a dataset with two hundred and eighty sensory measurements for leak detection and localization in water distribution systems. The data were generated via a laboratory-scale water distribution system that included (1) three types of sensors: accelerometer, hydrophone, and dynamic pressure sensor; (2) four leak types: orifice leak, longitudinal and circumferential cracks, gasket leak, and no-leak condition; (3) two network topologies: looped and branched; and (4) six background conditions with different noise and demand variations. Each measurement was 30 s long, and the measurement frequencies were 51.2 kHz for the accelerometer and dynamic pressure sensors, and 8 kHz for the hydrophone. This is the first publicly available dataset for advancing leak detection and localization research, model validation, and generating new data for faulty sensor detection in water distribution systems.
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