Ensuring the reliability and longevity of overhead power transmission lines is fundamental
to the stability and efficiency of modern electrical grids. As global energy demand rises
and the transition towards smart grid infrastructure accelerates, the need for advanced realtime monitoring technologies has become increasingly critical, particularly those capable
of operating accurately under challenging environmental conditions. This thesis presents
the development, implementation, and experimental validation of fibre Bragg grating (FBG)
sensors for structural health monitoring (SHM) of overhead line (OHL) conductors.
FBG sensors offer several advantages over conventional electrical sensing techniques,
including immunity to electromagnetic interference, multiplexing capability, compact size,
and suitability for remote sensing over long distances. This work exploits these advantages by
developing an FBG-based monitoring approach for key mechanical and thermal parameters,
including conductor sag, strain, temperature, and vibration, under varying mechanical loading
and thermal cycling conditions.
The novel contributions of this PhD thesis include the design and optimisation of a
mechanically robust FBG-based sag sensor mounting assembly for OHL conductors; the
laboratory characterisation of the sensor response to force and temperature over operating
conditions relevant to power networks; the assessment of measurement uncertainty associated
with force, temperature, wavelength, and sag estimation; the field deployment and validation
of the sensor system on an OHL test span at the Power Network Demonstration Centre
(PNDC); and the development of a fatigue-assessment methodology using FBG sensor data,
rainflow counting, Miner’s rule, and stress-life analysis to estimate the operational durability
of both the sensor and conductor. Experimental results confirm that FBG sensors are capable of reliably detecting structural
variations in OHL conductors, enabling early identification of changes associated with sag,
thermal loading, and vibration. The findings demonstrate the potential for integrating FBGbased SHM systems into future smart grid infrastructure, providing a lightweight, scalable,
and high-fidelity solution for continuous condition monitoring and predictive maintenance in
power transmission networks.
| Date of Award | 10 Jun 2026 |
|---|
| Original language | English |
|---|
| Awarding Institution | - University Of Strathclyde
|
|---|
| Sponsors | University of Strathclyde |
|---|
| Supervisor | Pawel Niewczas (Supervisor) & Grzegorz Fusiek (Supervisor) |
|---|