Fibre Health Monitoring Phase 2

Started

Other Power and Storage Technologies(Electricity transmission and distribution)

Applied Research and Development

ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)

Not Cross-cutting

Project Contact
National Grid Electricity Transmission

Network Innovation Allowance

Ofgem

01 January 2025

31 August 2026

ENA months

£350,000

Power

London

Network Innovation Allowance

Project Contact, National Grid Electricity Transmission

To address the above problem this project will carry out research into optical sensing technologies that can be deployed at key nodes on the fibre optic network in order to monitor the optical characteristics of the fibre network and derive asset health information. The measured data will be recorded over time and analysed together with other data sources such as environmental data to create an asset health model that allows predictive asset health monitoring and management.The focus in this project is on coherent OTDR and Brillouin OTDR inside a single demonstrator. The demonstrator will be installed on the NGET network for several weeks to months to monitor fibre optic cables of known asset condition and algorithms will be improved based on the derived information, with the goal to bring this to a TRL-8 by the end of the project. The scope of the project consists of further development of the prototype for an OPTEL fibre monitoring system and bring the product to a Technology Readiness Level (TRL) 8 state. The prototype was already conceptually tested in phase 1 of National Grids Fibre Health Monitoring project. The prototype consists of an Optical Time-Domain Reflectometry (OTDR), Brillouin OTDR (BOTDR) and Phase OTDR to monitor vibration, strain and temperature with the aim of assessing the current health condition of fibre optic cables and forecast future failures. The project will be delivered in two phases:Phase 1: Improvement of the various detection algorithmsWith the prototype hardware having proved its value in the phase 1 of the Fibre Health Monitoring project, the focus will now shift to the software to detect and eventually classify the various events. Both the phase OTDR and Brillouin OTDR are in focus here. This phase will end in an Alpha trial where the prototype is to be installed at National Grid Electricity Transmission (NGET) Enderby S/S to collect data over multiple weeks of measurements. Afterwards, a test report is to be written to summarize the findings and developments in this phase.Phase 2: Algorithm development continuation and geographical referencingIt is not projected that at the end of phase 1 that all possible events are readily detected and classified correctly. This will need lots of data to train the machine learning algorithms. Phase 2 will continue on the phase 1 work and findings for improving algorithms and as such the prototype detection performance. Additionally, geographical positioning of the detected events on a map is in scope for this phase of the project. This phase will end in an Beta trial where the prototype is to be installed at NGET Enderby S/S to collect data over multiple weeks of measurements. Afterwards, a final report is to be written including the test results of the Beta trail, to conclude the Fibre Health Monitoring Phase 2 project. The main objective of this project is to bring the prototype to a TRL 8 state for future deployment in the National Grid network. This is to be achieved by:Improvement of the coherent OTDR detection algorithm: With a coherent OTDR one can detect a wide range of events. For autonomous detection, a machine learning algorithm will be used to identify events along the network. During phase 1 first data was collected with the coherent OTDR in different weather conditions and this data will be used to train the algorithm to identify for instance rain, wind and thunderstorms. However, there is a wide range of applications and key to a robust ML algorithmis to have a lot of data for extensive training. Within phase 2 of the fibre monitoring project, the focus will be for the improvement of the detection algorithm to gather as much data as possible the ML algorithm.Improvement of the Brillouin OTDR detection algorithm: In addition to a coherent OTDR, the prototype product also includes a Brillouin OTDR. Brillouin measurements are ideal for the detection of strain and temperature. In phase 2 of the project, the focus will be on achieving autonomous event identification for Brillouin OTDR.Geographical referencing of events / faults: With theprototype it is possible to identify anomalies in the fibre network. In phase 1 it was for instance possible to identify locations with increased stress on the fibre. However, the prototype module provides the distance from the measurement device to the location, not a geographical location. In order to find out the geographical location of the fault, one needs to correlate the measurement data with geographical data.

The energy network transition will require more agile, flexible and interconnected networks underpinned by reliable communications networks in particular where services for protection and control are concerned. Operational fibre optic networks are reaching an age where some of the equipment is starting to fail whilst other parts of the network are intact and may be able to provide significant further service life. This project will examine enhanced optical sensing methods to detect and track the ageing process of fibre optic cables and associated fittings with the aim of providing accurate health information and the capability to forecast failures. The research will include new optical sensing methods as well as new algorithms to interpret the data and correlate to other data sources.?

09/04/25