<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/10710761-D7F9-4E2A-9620-93B25F89CAD9" ns1:id="10710761-D7F9-4E2A-9620-93B25F89CAD9"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/89426F03-5281-42EE-B95C-33AB90C2E545" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D22E2023-5235-467A-8071-0C577DB717FE" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/84BD9706-19C0-475C-9D45-1C24C828D373" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D22E2023-5235-467A-8071-0C577DB717FE" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/28456C35-D210-49F9-97D3-906D08820C41" ns1:rel="FUND" ns1:start="2018-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">104612</ns2:identifier></ns2:identifiers><ns2:title>RightLines - Overhead Line Equipment Monitoring</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>&amp;quot;The principle aim of this project is to develop a prototype NDT method based on guided wave technology (GWT) which will be able to identify damage which currently can not be detected -- at the locations where it is most likely to occur.

This project addresses the need for improving the method of identifying critical damage in overhead line equipment (OLE). Current non-destructive testing (NDT) methods of inspection are visual and are limited by the fact that they are often unable to identify critical damage because it is obscured by structural components. The limitations of current methods are widely recognised and have been highlighted in Network Rail's own challenge statements which states the need for intelligent assets and condition monitoring systems applied to OLE.&amp;quot;</ns2:abstractText></ns2:project>