Royal, A.C.D., Atkins, P.R., Brennan, M.J., Chapman, D., Chen, Huanhuan, Cohn, A., Foo, K., Goddard, K., Hayes, R., Hao, Tong, Lewin, P.L., Metje, N., Muggleton, J.M., Naji, A., Orlando, G., Pennock, S., Redfern, M., Saul, A., Swingler, S.G., Wang, Ping and Rogers, C.D.F.
Site assessment of multiple sensor approaches for buried utility detection
International Journal of Geophysics, 2011, . (doi:10.1155/2011/496123).
- Version of Record
The successful operation and maintenance of buried infrastructure within urban environments is fundamental to the conservation of modern living standards. Breakdown in supply of utilities is quickly noticed and requires a swift response to repair the network. Open-cut methods are predominantly used, in preference to trenchless technology, to effect a repair, or replace or install a new section of the network. This is, in part, due to the inability to determine the position of all utilities below the carriageway, making open-cut methods desirable in terms of dealing with uncertainty since the buried infrastructure is progressively exposed during excavation. However, open cut methods damage the carriageway and disrupt society’s functions. This paper describes the progress of a research project that aims to develop a multi-sensor geophysical platform that can improve the probability of complete detection of the infrastructure buried beneath the carriageway. The multi-sensor platform is being developed in conjunction with a knowledge-based system that aims to provide information on how the properties of the ground might affect the sensing technologies being deployed. The fusion of data sources (sensor data and utilities record data) is also being researched to maximise the probability of location. The project has reached a stage where the majority of the sensing technologies being developed for the multi-sensor device have undergone initial testing on site and this has shown some interesting findings. This paper describes the outcome of the initial phase of testing along with the development of the knowledge-based system and the fusing of data to produce utility maps
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