Monitoring buried infrastructure deformation using acoustic emissions
conference contributionposted on 2018-06-25, 13:12 authored by Helen Heather-Smith, Alister SmithAlister Smith, Neil DixonNeil Dixon, James FlintJames Flint, James Wordingham
Deformation of soil bodies and buried infrastructure elements (i.e. soil-structure systems) generates acoustic emission (AE). Detecting this AE by coupling sensors to buried structural elements can provide information on asset condition and early warning of accelerating deformation behaviour. A novel approach for deformation monitoring of buried steel infrastructure (e.g. pipes and pile foundations) using AE is described in the paper. The monitoring concept employs pre-existing, or newly built, buried steel infrastructure assets as waveguides. The propagation of AE through example pipes acting as waveguides has been modelled computationally using the program Disperse. A parametric study has been used to investigate the influence of key variables such as burial depth, surrounding soil type, internal environment, pipe diameter, wall thickness, frequency and mode type upon AE propagation and attenuation. Understanding the propagation and attenuation of AE is of fundamental importance for development of a monitoring strategy and specifically to determine the spacing of sensors deployed along infrastructure elements. The generation of AE due to soil-structure interaction mechanisms has been investigated using a programme of large direct shear tests of soil against steel plates under a range of conditions (e.g. soil type, plate surface conditions, stress level, strain rate). New, fundamental understanding of AE generation and propagation in buried infrastructure is enabling a framework to be developed for interpreting asset condition from AE measurements. The paper will introduce the approach developed, describe the parametric study of AE propagation and attenuation presenting example results, and show typical AE behaviour for soil-structure interaction obtained in the large shear tests. The implications for design of a monitoring framework will be discussed.
Helen Heather-Smith gratefully acknowledges the support of a DTA studentship for her doctoral work, and Alister Smith gratefully acknowledges the support of an EPSRC Fellowship (EP/P012493/1).
- Mechanical, Electrical and Manufacturing Engineering