Design and Development of a Focusing Radar Antenna for Transport Infrastructure Subsurface Investigation


   School of Engineering

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  Prof M Robinson  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

This project will develop and apply a novel focusing radar antenna to our pioneering rotational ground penetrating radar system which has been used to collect datasets of historic railway tunnel subsurface topography and is currently being used to investigate inland waterway locks.  

An improved antenna is required to improve the depth of penetration of the radio waves and to limit the beam width. The antenna will operate within 5cm of the infrastructure external wall and will investigate the subsurface. 

The main aims are to (i) distinguish structural features of interest from non-features; (ii) classify features as specific asset or defect types (e.g. void, crack, water ingress, etc.); (iii) characterize defects and return information of benefit to surveyors (e.g. dimensions, depths, material type, complexity etc.); (iv) automatically rank the severity of defects to convey to repair teams. Presently, we anticipate the research will produce a design for an antenna that will improve the existing point-cloud analysis architecture to accurately and reliably distinguish assets and such as ventilation shafts, refuges and catenary from defects including small-large voids, concealed shafts and water ingress, alongside background non-features including soil and healthy brickwork. Anticipated project outcomes would be design and prototype production of a novel antenna(s) capable of transmitting and receiving radio waves in different media such as concrete, masonry and soil. 

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society.  We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent.  We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices. 

Engineering (12) Physics (29)

References

Xiaoting Xiao, Guiyun Tian, Dong Liu, Mark Robinson and Anthony Gallagher “Developments in GPR Based NDT for Ballastless Track of High-Speed Railways” p227- 285, 2020 In Electromagnetic Non-Destructive Evaluation XXIII, Editors Tian GY and Gao B Publication Date October 2020. ISBN print 978-1-64368-118-4 ISBN online 978-1-64368-119-1
https://books.google.co.uk/books?hl=en&lr=&id=by4NEAAAQBAJ&oi=fnd&pg=PA277&ots=Cf0Z ULcq7P&sig=n2HNCOJ4Cw5gOj6MVJoBxAVaYYc&redir_esc=y#v=onepage&q&f=false

Mc Donald T, Robinson M, Tian G. Developments in 3D Visualisation of the Rail Tunnel Subsurface for Inspection and Monitoring. Appl. Sci. 2022, 12,11310.
https://doi.org/10.3390/app122211310
Thomas McDonald, Mark Robinson and GuiYun Tian, Spatial resolution enhancement of rotational-radar subsurface datasets using combined processing method. ICMSQUARE 2021 IOP Publishing Journal of Physics: Conference Series 2090 (2021) 012001 doi:10.1088/1742-6596/2090/1/012001

Liang Ge Changpeng Zhang; Guiyun Tian; Xiaoting Xiao; Guohui Wei; Ze Hu; Junaid Ahmed; Ju Xiang; Mark Robinson. “Current Trends and Perspectives of detection and location for buried non-metallic pipelines” Chinese Journal of Mechanical Engineering - Volume 34, Article number: 97 (2021) http://dx.doi.org/10.1186/s10033-021-00613-z

Xin Zhang, Liangxiu Han, Mark Robinson, Anthony Gallagher - A Gans-Based Deep Learning Framework for Automatic Subsurface Object Recognition From Ground Penetrating Radar Data IEEE Access (IF3.367), Pub Date : 2021-03-08,
DOI: 10.1109/access.2021.3064205

 About the Project