Detection of extended blockages in pressurised pipelines using hydraulic transients with a layer-peeling method

29th IAHR Symposium on Hydraulic Machinery and Systems

Zeng, Wei^1 ; Gong, Jinzhe^1 ; Lambert, Martin^1 ; Simpson, Angus^1 ; Cazzolato, Benjamin^2 ; Zecchin, Aaron^1

School of Civil, Environmental and Mining Engineering, University of Adelaide, SA

5005, Australia^1

School of Mechanical Engineering, University of Adelaide, SA

5005, Australia^2

关键词: Hydraulic transients;    Impulse response functions;    Infrastructure assets;    Layer peeling methods;    Method of characteristics;    Pipe wall thickness;    Pressurised pipelines;    Water distribution system (WDSs);   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/240/5/052019/pdf
DOI  :  10.1088/1755-1315/240/5/052019

来源: IOP

【 摘 要 】

Water distribution systems (WDSs) are one of society's most important infrastructure assets. They consist of buried pipes that are often old and their condition is extremely difficult and expensive to determine. This research proposes a non-invasive layer-peeling method using hydraulic transient waves to detect extended blockages in pressurised pipelines. In the numerical study, hydraulic transient pressure waves are injected into a pipeline at a dead-end. Wave reflections caused by multiple extended blockages (uniform and non-uniform) are simulated using the method of characteristics (MOC). The impulse response function (IRF) of the pipeline is then obtained using the simulated pressure response at the dead-end. The original layer-peeling method previously applied to tubular music instruments is further developed by considering the differences between the instruments and pressurised pipelines (boundary conditions, fluid properties). Using the IRF and the modified layer-peeling method, the internal pipe diameter values are estimated section by section from the dead-end to the upstream end of the pipeline. The blocked pipe sections are then accurately identified from the reconstructed pipe wall thickness distribution profile.