Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_NGN_186 | |
| Title | Highly Portable GPR | |
| Status | Completed | |
| Energy Categories | Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 100%; | |
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Physics) 50%; ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 50%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Project Contact No email address given Northern Gas Networks |
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| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 October 2016 | |
| End Date | 01 October 2017 | |
| Duration | 12 months | |
| Total Grant Value | £79,990 | |
| Industrial Sectors | Technical Consultancy | |
| Region | Yorkshire & Humberside | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , Northern Gas Networks (100.000%) |
| Web Site | http://www.smarternetworks.org/project/NIA_NGN_186 |
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| Objectives |
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| Abstract | Current asset detection and identification methods include Ground Penetrating Radar (GPR) which is used to locate buried assets within the utility distribution networks and construction industry. These devices however are often trolley mounted, weighing over 20kg, displaying raw GPR data on a separate screen. Interpretation is therefore undertaken by a skilled operator leading to surveys being facilitated by specialist third party companies. Also due to the cumbersome size of the unit it can render many deployments inaccessible, especially in rural areas and across difficult terrain. There is therefore a reduction in use due to difficulties in GPR deployment and interpretation of data. A lightweight GPR unit either handheld or UAV mounted will significantly increase the assets that can be inspected and the quality of output achieved. The need for a skilled operative on the ground will be progressively reduced as the data can be gathered and sent remotely to the office based expert for immediate interpretation both reducing costs and speeding up the process of delivery. Over time Deep Learning algorithms will reduce this need further. It is proposed to further develop an innovative Ground Penetrating Radar unit;Small size - on board backup data store, weight - 850g, size - 250x250x180mm WIFI - the unique real time Wi-Fi capability could facilitate immediate processing, validation and analysis of data allowing immediate refinement of the collection process and avoid delays and potential costly revisits GPS - integration of accurate Real Time Kinematic (RTK) based GPS to allow asset positioning Data - development of data structures to allow importing of data into current 3D GEO modelling softwareDatabase - begin development of a foundation empirical database of featuresGraphical display - development to produce easily decipherable 2D or 3D graphical outputsAdaptable - adapt sensor unit for highly portable deployment including hand held, trolley mounted and unmanned aerial vehicle (UAV)Automatic interpretation - begin development of algorithms to interpret and identify buried assets including change comparison against existing recordsThis system will allow increased deployment of GPR via a broader range of methods across the distribution networks. In time it will allow the network operator to quickly, accurately and easily; locate buried utility assets; detect voids; determine depth of cover; determine reinstatement thickness/cavities/condition; survey proposed pipeline route for archaeological/historical interest; reducing the need fora site based GPR expert with minimal environmental impact and in difficult to access locations. Concrete utility structures may also be possible to survey without the requirement to work at height. Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above |
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| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 21/08/18 | |
