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Innovative Condition Monitoring of Electricity Transmission Assets:
from science based archaeology to monitoring environmental risks on infrastructure

Environmental factors can accelerate corrosion, e.g. air pollution and salinity in coastal areas are known factors. It is therefore important to understand the relationship between various environmental factors and corrosion to inform asset management policy. National Grid Electricity Transmission (NGET) network alone has 21,990 steel lattice towers that supports the overhead power lines in England and Wales.

NGET inspects the condition of around 3650 steel lattice towers each year. Owing to restrictions on land access as well as the sheer volume of assets, data is captured via colour imagery taken from helicopters. The processing of images to classify the extent and nature of corrosion is a manual task.


The grading of the level of corrosion is performed by manual inspection of the images. It was found that the changing light conditions can reduce the accuracy of inspection from colour images. Therefore, 10 percent of these assets are then inspected manually by engineers by climbing up the towers for verification of trouble areas.

The stakeholders are:

1) The National Grid - national electricity transmission system operator

2) OPUS International Consultants Ltd. - a global infrastructure development and asset management company

3) Mosdorfer CCL systems Ltd. - a manufacturer of overhead power line products

Addressing the Challenge

Overall, the grading of steel health is subjective and time consuming, posing health and safety risks to inspectors. The proposed project aims to translate technology and methods developed for science-based archaeology in the form of remote imaging at standoff distances to condition monitoring of infrastructure in the energy sector, demonstrating the impact of research in NERC remit to the energy and infrastructure sector and UK economy, initiating step change in condition monitoring of electricity transmission assets.

The proposed innovation is timely because it promises automated data capture and analysis with the prospect of producing more quantitative and reliable results.

Making a Difference

The ability to track condition over time will support an understanding of how these assets perform and deteriorate throughout their lifecycle, and support the ability to predict the optimal time to repair and replace them. Such predictive ability supports a least lifecycle cost paradigm - cost savings that can be passed on to consumers.

With demands to continuously improve working practice safety, accuracy of asset surveys and therefore lifecycle costs, the innovation delivers significant maintenance, planning and cost benefits necessary for critical infrastructure assets and society as a whole. Similar asset monitoring and management issues cross-cuts the infrastructure and energy sectors, ranging from railway tracks, bridges, ships, off-shore platforms to pipe lines.


Academic Investigator:   

Professor Haida Liang (Nottingham Trent University)

Research Fellows:           

Dr Alessandra Vichi (Nottingham Trent University)

Dr Sotiria Kogou (Nottingham Trent University)

Dr Florence Liggins (Nottingham Trent University)

Dr Chi (Sammy) Cheung (Nottingham Trent University)

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