AI-Assisted Design & Optimization for Predictive Maintenance: A Case Study using Deep Learning and Search Metaheuristics for Structural Health Monitoring in Aviation

One of the classical solutions to maintain the aircraft structural integrity is to rely on the analysis of non-destructive testing (NDT) inspector with various inspection methods. However, it is relatively expensive in matter of time and costs to train human resources until the certification is reached. Further, in majority of the cases of...

Shearography non-destructive testing and defect characterisation of thick composite structures

THICK composite materials, e.g., thickness of more than 50 mm, are increasingly being used across diverse industry sectors owing to their significant advantages of weightsavings, superiormaterial properties and load-carrying capability. These materials tend to be adopted in safety-critical applications such as large primary or secondary load...

Assessment of bolted connections for supporting structures of offshore wind turbine towers: Mechanical performance and structural health monitoring

In the past two decades, offshore wind has emerged as a new source of renewable energy. This highlights the requirement for the utilisation of larger and more efficient offshore wind turbines (OWTs). The connections used in support structures of OWTs are critical to ensure the excellent structural performance of OWFs. An alternative option is...

Development of highly scattering distributed fibre optic sensing for structural health monitoring

In this thesis, fibre optic sensing has been investigated as an important technique for structural health monitoring. Distributed fibre optic sensing based on Rayleigh scattering is a fibre optic sensing technique to achieve the spatially continuous strain monitoring for critical locations for the structures. However, the Rayleigh backscattering...

Fibre Optic Shape Sensing and Load Monitoring of Adaptive Aerospace Structures

The aerospace industry is an ever-evolving field that has seen many technological advances over the past decades. The desire for aircraft to be not only efficient and reliable but also cheaper and safer has brought about many proposals across the industry. One of these advances is towards morphing aircraft wings to make wings lighter, more...

Automated Defect Analysis using Optical Sensing and Explainable Artificial Intelligence for Fibre Layup Processes in Composite Manufacturing

In modern aircraft, structural lightweight composite components are increasingly<br/>used. To manufacture these components in a costeffective way, robust production systems for the manufacturing of complex fibre composite components are necessary. A rather novel but already established process for fibre material deposition is the Automated Fibre...

Modelling of Ultrasonic Array Signals in Anisotropic Media

There has been a steady increase of composites and anisotropic materials in primary aircraft structures over the years. This increase is driven by the high strength to weight ratio of such materials leading to lighter and more efficient aircraft. As the uptake of such materials keeps increasing so does the complexity in geometry and manufacture...

Accurate structural health monitoring in composites: With fibre Bragg grating sensors

Compared to metals, composite materials offer higher stiffness, more resilience to corrosion, have lighter weights, and their mechanical properties can be tailored by their layup configuration. Despite these features, composite materials are susceptible to a diversity of damages, including matrix cracks, delamination, and fibre breakage. If...

Ultrasonic Health Monitoring of Thermoplastic Composite Aircraft Primary Structures

The adoption of composites as aircraft primary structural material has created a real need for a new aircraft maintenance philosophy to enable almost real-time structural condition assessment. It is thus crucial to develop structural health monitoring (SHM) systems capable of performing damage diagnostic and remaining useful life prognostic. At...