- 0.1 Lucy Dougill
- 0.2 Melody Png
- 0.3 Adam Gilmour
- 0.4 Matt Chandler
- 0.5 Qin Feng
- 0.6 Luke Smith
- 0.7 Joshua Aigbotsua
- 0.8 Meirbek Mussatayev
- 0.9 Weixin Wang
- 0.10 Serhat Bakir
- 0.11 Connor Challinor
- 0.12 David Harra
- 0.13 Ewan Nicolson
- 0.14 Chris Stone
- 0.15 Nina Sweeney
- 0.16 Nikolay Pilashev
- 0.17 Mikolaj Mroszczak
- 0.18 Yangjie Chen
- 0.19 Zubeir Ebrahim Saib
- 1 Aligned Students
University: Bristol Supervisors: Professor Anthony Croxford & Professor Paul Wilcox
PhD Project: Visual Vibrometry and its Application to NDT Through the Use of Various Video and Signal Processing Techniques
The aim of my project is to explore how large area visual monitoring approaches may be employed to monitor the state of structures through combining the use of ultrasonic guided waves and visual systems. The combination of the visual systems ability to monitor large areas and ultrasonic guided waves ability to penetrate parts at depth that provide additional useful information regarding the structural health of a specimen.
One key focus is to investigate how the sensitivity of the visual methods and their sampling capabilities may be pushed to their limit in order to measure small displacements arising from useful ultrasonic frequencies.
University: Imperial College London Supervisor: Dr Bo Lan
EngD Project: Material Characterization using Ultrasonic Testing
The aim of this project is to explore novel developments in the area of ultrasound to characterize critical microstructures of engineering materials, with a particular focus on diffuse ultrasound. The project comprises of: 1. Developing theoretical and computational models to understand the behaviour of diffuse ultrasound to microstructures 2. Conducting experimental validations as well as defining potential applications of this technique. Specifically, this project focuses on Ti-64 alloys in development of a generic solution that could also be applicable to other materials.
University: Strathclyde Supervisor: Dr Gordon Dobie Sponsor: BAE Systems Submarines
EngD Project: Robotic Inspection of Complex Welds
Current semi-automated NDT practices often require a great deal of human interaction or interference. This project aims to develop robotic solutions for industrial applications by reducing the amount of hands-on inspection time and through improving the capabilities of automated procedures. We also aim to develop more intelligent inspection systems by incorporating in-situ NDE data into the decision making of any robotic application.
University: Bristol Supervisor: Professor Anthony Croxford
PhD Project: Ultrasonic Inspection for Complex Geometry
Current ultrasonic inspection methods typically rely on line-of-sight access to the region being inspected within a material. In general, this means that geometrically complex components are challenging to inspect in-situ. This project aims to explore how regions of material without line-of-sight access can be inspected by exploiting the reflections of ultrasonic waves from the component geometry, starting with simple geometries before moving on to complex cases. This would enable a wider range of components to be inspected in service, reducing downtime.
University: Bristol Supervisor: Professor Bruce Drinkwater Sponsor: China Scholarship Council
PhD Project: Novel ultrasonic coupling materials
In ultrasonic non-destructive testing (NDT) the use of a coupling liquid or solid between an emitter and the test structure is universal. These layers allow the energy to be transmitted into the structure as well as allowing reflected energy to be received. This project aims to build on recent advances in materials and 3D printing to develop novel coupling layers.
University: Warwick Supervisor: Professor Steve Dixon
PhD Project: Ultrasonic Flow Measurement
Thin-walled pipes are widely used for carrying fluids in domestic and industrial environments, but clamp-on ultrasonic flow measurement is difficult because the pipes host guided waves. The aim of this project is to understand the behaviour of leaky guided waves in the pipe-fluid system to enable reliable flow measurement. The received signals are complex, so the first task is to identify the paths by which the ultrasound can reach the detector through experiments and computing. Then, a meter can be developed which utilises this knowledge to make a transit time flow measurement.
University: Bristol Supervisors: Professor Bruce Drinkwater & Professor Mahdi Azarpeyvand Sponsor: Baugh and Weedon
EngD Project: Low-frequency Vibration Inspection of Sandwich Composites
One-sided in-service inspection of certain composite structures (honeycomb-, balsa- and foam-core sandwich) can be successful using a low-frequency vibration method but defect detection is limited, and classification of defects is not currently supported. This project aims to establish a new low frequency inspection method, termed ‘Thickness Resonance’, which has the ability to resolve far-side defects in certain sandwich composite structures. Defects classification, including determining their depth, location and size will be achieved based on comparison with modelled low-frequency responses of a range of structures with different defect types.
University: Bristol Supervisor: Dr Robert Hughes & Professor Paul Wilcox
PhD Project: In-line Eddy-Current Characterisation of Carbon Fibre Composites
This project will explore how the material and environmental properties influence the detectability of flaws and structural properties.
The aim and objectives of this project are:
- Determine how layup structure alters the effective conductivity of the structure.
- Characterise differences in ECT response to cured and uncured carbon fibre composite materials.
- Develop advanced measurement & data-analysis techniques for evaluating structural properties such as fibre orientation, stacking sequence and fibre density variations.
Specifically, this project focuses on evaluating of the influence of inspection environment as well as the improving the probe design. Specific requirements for the probe design:
- have a high sensitivity to detect small defects with a very good signal-to-noise ratio when handled with conventional ECT equipment.
- be capable of detecting distinct kinds of defects (morphology and locations).
- be easily customizable and affordable.
University: Bristol Supervisors: Dr Jie Zhang and Professor Paul Wilcox Sponsor: China Scholarship Council
PhD Project: Metallic material grain structure characterisation using ultrasonic arrays
A major barrier to characterise materials at the defect early development stage is the lack of techniques to measure material grain structure, mainly including grain size and its texture. This limits the further understanding of the ultrasonic wave interactions between material grains and defects and their ultrasonic signal and image performance. The aim of this project is to develop ultrasonic array techniques to enable the material grain structure to be measured before defect detection. The key is how to use ultrasonic phased arrays to capture data, control wave beamforming and postprocess the data to extract useful information such as material gain size and its texture.
University: Bristol Supervisor: Professor Paul Wilcox PhD Project: Guided wave monitoring of girth-welded specimens using artifical intelligence
University: Imperial Supervisor: Professor Fred Cegla – Sponsor: NDT Global EngD Project: Coded Excitation of Ultrasound for Improved Signal Acquisition in Pipeline Inspection Robots
University: Strathclyde Supervisor: Katy Tant PhD Project: Ultrasonic Characterisation of Micro-Texture Regions In Titanium Alloys
University: Strathclyde Supervisor: Charles MacLeod PhD Project: Advanced NDE in Future Oil and Gas Inspection
University: Bristol Supervisors: Professor Anthony Croxford & Professor Bruce Drinkwater PhD Project: Acoustic Streaming – Developing a Fundamental Understanding of Acoustic Streaming and its Use for Flow Manipulation and Control
University: Strathclyde Supervisor: Dr Charles MacLeod
Sponsor: Peak NDT
EngD Project: In-Process Adaptive NDT for Fast & Flexible HVM
This project aims to improve the flexibility, accuracy and speed of in-process High Value Manufacturing (HVM) robotic inspection and control operations, with a focus on three key challenging applications: arc welding, wire and arc additive manufacturing (WAAM) and complex carbon fibre composites.
University: Bristol Supervisor: Professor Paul Wilcox Sponsor: Rolls Royce
EngD Project: Automated Sentencing for Complex Shaped CFRP Components
Carbon fibre material is increasingly being considered for aero-engine components. Such components are being designed to withstand high loads and to have more complex shapes, making inspection for material integrity both more important and more difficult. New analysis techniques are required and are being developed for defects such as porosity. However, such techniques create large data sets that become time consuming and difficult, or impossible, to interpret by a human inspector.
The aims of the project will include: 1. Investigation of new quantitative data analysis techniques for porosity detection in CFRP. 2. Development of data fusion methods to allow extraction and presentation of information from multiple data sources. 3. Automated interpretation of 3D data.
University: Imperial College London Supervisor: Dr Peter Huthwaite Sponsor: Guided Ultrasonics Limited (GUL)
EngD Project: Measurement Interpretation for Guided Wave Testing
The ongoing development of Guided Wave Testing of piplelines is increasingly generating large amounts of measurement data that needs to be interpreted. This includes change detection from repeat measurements acquired from permanently-installed transducer equipment, the automation of the interpretation of routine measurements, and the assessment of complex signals to extract image or critical parameter information. The pressure to develop software tools to aid these tasks is amplified by the increasing availability of the large quantities of raw data via cloud communications. This project will work on developing methodologies and implementing these in software tools to address these needs.
University: Bristol Supervisor: Professor Anthony Croxford
PhD Project: Autonomous NDT
The aims of my project and to work closely with University spin out company ‘Inductosense‘, who developed innovative wireless, battery free, and permanently installed sensors for non-destructive testing. I will develop a robotic platform that ultimately aims to deploy sensors and take measurements autonomously with given locational information of where the sensors are permanently installed, which hugely increases the accessibility and reduces the cost of operation.
To achieve the goal, accurate positioning and perfect alignment between the measurement probe and sensors are required.
Zubeir Ebrahim Saib
University: Bristol Supervisors: Professor Bruce Drinkwater & Professor Anthony Croxford
PhD Project: Early detection and characterisation of defects using nonlinear ultrasound
One of the grand challenges in non-destructive testing (NDT) is the measurement of the remaining life of a structure.
Up to now, most NDT methods aims to detect and characterise relatively large defects which occur at the end of the life of a structure using linear ultrasound. Potential use of nonlinear ultrasound has been demonstrated in the literature to be sensitive to early formation of defects, such as microcracks. Different techniques exist, namely second harmonic generation and diffuse field. However, whilst these new nonlinear imaging or defect characterisation techniques have shown promising results in laboratory experiment, they have not yet reached the sensitivity to image the build-up of material nonlinearity due to aging, or other effects such as thermal or plastic deformation.
This project aims to develop the required modelling tool to fully understand the measurement scenario and devise experiments to extract material nonlinearity to predict failure at an earlier stage.
University: Imperial College London Supervisors: Dr Bo Lan & Professor Mike Lowe Sponsor: Rolls Royce
EngD Project: Phase Characterisation of Nickel-Based Superalloys using Ultrasound
Ultrasonic methods are widely used in NDE for defect detection, but there has been increasing research in using ultrasound for bulk material property characterisation, particularly for aerospace engine materials. Techniques have been successfully applied for use with titanium alloys, and my research will focus on how these can be further developed for phase characterisation of nickel superalloys, which are widely used for high temperature regions of aerospace engines.
University: Imperial College London – Supervisor: Dr Peter Huthwaite Industrial Sponsor: Guided Ultrasonics Limited (GUL)
PhD Project: Model-based Inversion of Guided Waves in Pipes
My project will explore full wave inversion using finite element modelling, focusing on guided waves. This will be a model building tool that will allow for the quantitative detection and imaging of defects when given a measured signal, while maintaining the long range sensing benefits of guided waves.
University: Manchester Supervisor: Professor Anthony Peyton Sponsor: Tenaris
PhD Project: Electromagnetic Non-Destructive Testing for Inspecting the Microstructure of High Performance Ferritic Steels
New techniques to measure the microstructure of a material in a non-contact non-destructive fashion can lead to a dramatic improvement in the understanding of the material and its behaviour during processing and in-service, and an ability to control or predict the material properties. This project will consider advanced magnetic techniques for inspecting the microstructure of high value ferritic steels during manufacture and in service, focussing on applications of strategic importance to industry. The key aims are to establish robust relationships between microstructure and the magnetic properties and to devise sensors which exploit these relationships for use in the field.
University: Manchester Supervisors: Professor Timothy Coates & Dr Martin Fergie
PhD Project: Machine learning to locate defects in ultrasonic inspection images
It is important that manufactured components are inspected to identify defects which may cause early failure, particularly in safety critical systems. Non-destructive techniques, such as ultra-sound, are used regularly to be able to see below the surface to identify hidden defects. This project aims to develop automatic techniques to help identify the defects. The student will combine image analysis and machine learning methods to build a system that can reliably distinguish between normal parts and regions with abnormalities. This project will investigate the application of novel analysis techniques to ultrasonic NDE inspection, aiming to support the analysis of phased-array or Time-of-Flight-Diffraction images.
The project is actively supported by BAE Systems Maritime who deploy these techniques in a large scale manufacturing environment. The benefits of a robust automated analysis process would be very significant and could potentially reduce the inspection cost and duration for large scale welded structures across many industrial sectors.
University: Strathclyde Supervisor: Charles MacLeod
PhD Project: Advanced non-destructive testing of blade manufacturing defects
Wind turbine blades are one of the most costly and complicated components of the wind turbine. Now approaching 100m in length, they are manufactured using carbon and glass fibre reinforced polymer composites. Non-Destructive Testing (NDT) methods are utilized to identify any potential defects so to reduce potential asset outages, operational maintenance costs and extend lifetimes.
Ultrasonic testing techniques are a promising NDT method for blade inspection, due to volumetric inspection capability, but current uses are limited due to complexities with the data/image analysis typically performed by trained experts. The aerospace industry has pioneered investigation into contactless scanning methods for complex geometry inspection, coupled with detection algorithms and machine-learning techniques. Investigation and optimisation of these methods to wind turbine blades will enable more efficient and cost-effective inspections resulting in overall benefits for clean energy production.
A review of current ultrasonic NDT techniques for composite materials will be conducted and the most applicable for the wind industry identified. These will be tested on small blade samples, provided by industrial partner Siemens Gamesa Renewable Energy. Following on from this, processes are to be upscaled with the aim of developing mature and fully automated inspection, and image analysis, techniques used in large-scale blade manufacturing.
University: Strathclyde Supervisor: Dr Gordon Dobie
PhD Project: Utilise a Multi-Agent System and EMAT’s to carry out thickness measurements and defect detection within ferromagnetic structures
University: Strathclyde Supervisor: Dr Theodosia Stratoudaki PhD Project: Laser Generated and Detected Ultrasound for NDT
University: Strathclyde Supervisor: Dr Theodosia Stratoudaki PhD Project: Volumetric imaging for Laser Induced Phased Arrays (LIPA)
University: Strathclyde Supervisor: Professor Gareth Pierce Sponsor: TWI PhD Project: Advanced End Effector System for Robotic Inspection Systems