Speaker
Description
Ageing water infrastructure that includes water and sewer pipes often suffers from defects which are difficult to detect with water industry state of the art techniques. Wall thinning or delamination (external/internal) in pipe walls provides a challenging boundary value problem in 3D cylindrical system. Non-contact low frequency acoustic methods offer robust and easy to deploy technology capable of detecting in gases or liquids hidden changes in the pipe conditions. In the present work, a Green’s function approach under low-frequency assumption has been adapted to deal with a waveguide (pipe) problem with localized elastic interface backed by fluid cavity, which resembles wall thinning or delamination. The developed methodology is integrated into non-contact pipe condition monitoring tools used in the following related research projects: (i) AI:LINER, an EU multi-institutional project that combines novel acoustic solution, CCTV data, AI-based failure detection, and in-situ monitoring techniques to enhance the asset management life cycle of sewer networks; and (ii) an EPSRC-funded project, to develop bio-inspired micromachine sensors for measuring acoustic quantities.