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Projects: Projects for Investigator
Reference Number NIA_NGN_042
Title Visual & Acoustic Leakage Detection
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%;
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 50%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Project Contact
No email address given
Northern Gas Networks
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 June 2013
End Date 01 September 2013
Duration 3 months
Total Grant Value £141,250
Industrial Sectors Energy
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_042
Objectives To objective of the assessment to reduce the number of long duration escape jobs on the West Yorkshire escape log from 70 to 40 over a 12 week period. To establish a full cost benefit analysis on the use of this technique. To establish the safety procedures required for deploying this technique and what controls are required to ensure increased safety is maintained To assess the skills and training required to deploy this equipment, with recommendations for full deploymentReduction in reinstatement requirement Measure the impact on NRSWA Measure the impact on Customer - especially around traffic disruption. Produce a detailed summary report for each job detailing findings, results and outcomes. To reduce the cost of a long duration repair by over 33% To reduce the number of long duration jobs on the escape log by 57% To complete a minimum of 100 jobs within a 12 week period capturing empirical evidence of results To produce a final report within 5 weeks of the project completion detailing summary of the project, recommended changes to procedures, deployment changes required and draft business case for roll out.
Abstract Detecting leakage were no immediate obvious solution is available, typically city centre locations, congested highways or locations with particular specific engineering difficulty, repairs can be expensive to undertake requiring significant resources, disruption to customers and can take a long time to resolve. Leakage detection is currently undertaken by using a Wheatstone Bridge based detector to pinpoint the closest location of the escaping gas from the surface. While in the majority of cases this technique can quickly provide good guidance to engineering teams on the exact excavation location point to undertake the repair. In situations of engineering difficulty these indications can be some distance from the mains escape point, leading to "dry" holes, extended excavations or trial holes to assist in locating the actual leakage point. To insert from a remote location an interchangeable hi-resolution CCTV, together with a hydrophone leakage detection indicator in the gas mains system. To undertake real time analysis of a significant length of gas main internally to pick up audibly gas leaking from the network. Insert a ruggedized CCTV system with an on-board hydrophone with the adjustable sensitivity to pick up gas escaping from the network. The system includes a pressurised launch and feed system which allows safe and consistent feeding of the system during live insertion work. There are no products currently available within the gas industry that uses multi sensor technology with the robustness and quality required. The hydrophone and software is sensitive enough to detect the smallest of leaks within low pressure gas distribution systems. Full leakage acoustic signatures can be displayed graphically or using the conventional audio output as headphones and HD CCTV live images allow the operator to validate the full survey. A sound recording will be made prior to repair excavation and will maintain recording during repair process. This will develop new learning of typical sound profile for different leakage levels and types.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications (none)
Final Report (none)
Added to Database 17/12/18