LeakVision is a novel leakage detection sensor. The system is used for the inspection of features to indicate the presence of leakage from pipeline features (joints, connections & defects). This project builds on and is de-risked by a successful and previously completed NIA project completed by Cadent (NIA_CAD0019) and additional prior and post independent work by Synthotech Ltd. The additional work developed a proof of concept demonstration unit that has shown the ability to indicate leakage within a simulated leakage scenario.
Objectives
• Develop SLS concept (3D printed) - Concept should provide real world data on performance within laboratory test and simulated rigs for data on applicability of technology to NGN.
• Create gas verification rig - Provide a gas rig to test project assumptions and provide data and calibration. The rig will allow the concept to be assessed for suitability.
• Complete modelling - Provide detailed data modelling to allow the optimisation of the detection within the project.
• Create prototype - Create a prototype system for deployment across the network to assess the detection, operation and potential of the technology in a real-world environment.
• Completion of gas trialling - Provide a minimum of 10 and maximum of 20 network field trials for the assessment of the LeakVision technology within the real-world environment. This will be summarised in a short report.
Learnings
Outcomes
The LeakVISION technology developed throughout NIA_NGN_256 makes use of thermography to analyse and highlight leakage by directly scanning the pipeline and pinpointing the area.
The thermal image sensor can be inserted into a pipe via a robot base camera system similar to that already deployed by NGN (STASS).
TTP collaborated with NGN & SynOvate to develop a leakage framework to analyse the output data from LeakVISION usage on the live network.
Rosen have collaborated with NGN & SynOvate to assess current leakage models utilized by the UK Gas Networks and have worked to design and publish a revised leakage model based upon up-to-date pipeline condition populations.
NGN, SynOvate & Rosen delivered a joint stakeholder engagement event to raise awareness of LeakVISION within the UK Gas Industry and to share key learning points with regards to leakage identification and modelling.
Field trials will continue beyond project closure to continue to gather evidence to support with G23 Full Network Approval on Northern Gas Networks System. Additionally, further data gathered during the field trials will continue to validate the leakage models and frameworks reviewed and developed throughout this project.
NGN & SynOvate are working closely to understand in greater detail deployment scenarios for BAU usage.
Lessons Learnt
- Good communication throughout project delivery between all project partners enabled for progress to be controlled and any risks to be identifying and mitigated against in a timely manner.
- Information sharing and external communications were limited during the bulk of the project due to the impact of COVID-19, future projects should assess the need for a varied communication strategy.
- The system passed preliminary ATEX design review and therefore should be suitable for full accreditation for use when functional field testing is complete.
- The Project suffered difficulties with identifying and delivering field trials in a more timely manner due to issues with identifying work that would provide sufficient and beneficial evidence for the project, this was relieved by working closer with NGN Operational Teams and utilization of the existing STASS Team.
- Use of the STASS Team, who are already highly experienced in using robotics on NGNs network resulted in a smooth transition and minimal operational issues when deploying LeakVISION for field trials.
