Cohort 3

Matthew Riding 

University: University of Strathclyde

Supervisor: Dr Theodosia Stratoudaki & Dr Charles MacLeod Project: Novel schemes of laser ultrasound deployment and data analysis to solve industrially relevant NDE challenges

Laboratory experiments with laser ultrasonic testing (laser UT) have demonstrated the ability to detect and characterise manufactured defects within solid components in fully non-contact schemes.  Demonstrations of advanced laser UT techniques, such as laser-induced phased array inspection, have until now mostly been performed on simple samples with favourable acoustic properties and exaggerated, artificial defects.  Whilst such simple test samples are ideal for experiments focussing on fundamental technique development, a wider range of sample materials, geometries, defects and inspection problems must be explored in order for advanced laser UT techniques to mature further.  This project therefore aims to perform advanced laser UT experiments on novel samples, identify issues limiting the information obtained and then apply novel approaches to both experimental configuration and data analysis to demonstrate the applicability of this technology to industrially relevant NDE challenges. 

Gala Dalgety

University: University of Warwick

Supervisor: Dr Rachel Edwards Project: Automated Implementation of EMAT Inspection 

This project essentially looks into the intelligent operation of robots with non-destructive testing (NDT) capabilities. This will include building on previous developments in making miniaturised electromagnetic acoustic transducers (EMATs) capable of generating and detecting shear horizontal (SH) waves. Advantages of this include improving spatial resolution, and making implementation onto a robotic platform simpler, particularly for inspection of ferritic steel. However, the signal to noise ratio (SNR) of these techniques are smaller than other ultrasonic alternatives and it will be essential to explore how to improve signal analysis. One of the ways to improve SNR will be to look into focusing and phasing the SH waves and taking advantage of any directivity the EMATs have. Other solutions to improve SNR to be explored include utilising other wavemodes and sensing techniques and performing data fusion, looking at robot scanning techniques to give high probablilities of defect detection, and the use of multiple scans to find if there is a defect in the area and then rescan the areas with a high probability of a defect.

Martha Turvey

University: University of Warwick

Supervisor: Rachel Edwards Project: Liquid crystal sensors for ultrasound detection

Liquid crystals can be used to make a passive detection sensor for ultrasound, providing a visual image of the propagation of ultrasound through the sample. Demonstration of the sensor has focused on analysis of the resonant modes of a piezoelectric transducer, and visualisation of longitudinal waves passing through a sample. Although the technology is at a low technology readiness level (TRL), several potential avenues are ready for exploitation. This project will identify the key areas for development, look at potential applications, and develop the sensors such that they can be used for non-destructive testing (NDT). 

Shaun McKnight

University: Strathclyde Supervisor: Professor Gareth Pierce

Phd Project: Machine Learning for NDE Inspection

Ultrasonic NDT methods are critical in the testing process of manufacturing for composite aerospace components. There are ambitions to automate this process, however the requirement for manual interpretation of NDT results remains a bottleneck in the testing. My project aims to address this challenge by developing Machine Learning algorithms to allow for automatic interpretation of results. This project hopes to integrate with other non-destructive testing projects with the overall aim of automating the complete testing process. 

Mo Zubayr

University: Nottingham Supervisor: Adam Clare

Phd Project: Unveiling materials with robotic electrochemistry

The aim is to automate the testing of metals using an electrochemical jet to both make measurements and to machine the surface using industrial robotics. Electrochemical jet machining can be used to deposit, remove, and pattern material on the surface of a wide range of metals. The size of the jet as well as other parameters such as current can be used to control the surface area of material removal and addition. One of the objectives is to make measurements during machining and adjust the process accordingly. Measurements made can tell us how much material was removed as well as the roughness for example without having a dedicated process to determine such properties. Usually, such analysis would be done after machining and is usually outsourced to a specialist institution with specialized equipment and training individuals performing the analysis. The main objective will be to research and develop a system that can be integrated into a manufacturing process and perform analysis and adjustment autonomously.

Martin McInnes

University: Strathclyde Supervisor: Dr Ehsan Mohseni

PhD project: Automated in-process inspection of additively manufactured components using ultrasonic testing and eddy currents 

The aim is to automate eddy currents and ultrasonic testing using industrial robots. Throughout the project, the plan is to simulate, design and build electromagnetic and ultrasonic sensors in which they will be integrated with automated systems and their performance evaluated through the inspection of aeroplane composite materials.   

Lily Tu

University: Bristol Project Supervisor: Professor Paul Wilcox

Phd Project: Laser induced 2D phased array for composite material inspection

Laser induced phased arrays (LIPAs) have several advantages over traditional piezoelectric ultrasound arrays in terms of their non-contact, couplant free nature, and their ability to change array geometry during an inspection as the element positions are not fixed. The proposed research will design a 2D LIPA for inspection of defects in composite materials using simulated data and implement the array design in experiments. The successful outcome of the research will demonstrate the suitability of using LIPA as 2D array in improving defect inspection and characterisation in composite material. 

Laurence Clarkson

University: Imperial Supervisors: Dr Frederic Celga

Phd Project : Estimation of internal pipe wall temperature

There is concern that rapid temperature changes in the primary cooling circuit of reactors can induce thermal fatigue that can be detrimental to the overall life of components in the primary circuit. It is therefore desirable to monitor the number and magnitude of cross wall temperature changes in these components so that one can better estimate the magnitude and number of stress cycles that a component experience to predict the overall life of the components. This project aims to build on the outcomes of a recent feasibility study to enable real-time monitoring of temperature wall gradients in primary circuit components under realistic conditions (up to 350°C). 

Harry Gover

University: Strathclyde Supervisors: Gareth Pierce & Charles MacLeod

PhD Project: Collaborative robotic control and path planning in dynamic environments 

 The widescale uptake of industrial robotics depends on the robot’s ability to operate accurately and safely while sharing a workspace with humans; such robots are referred to as ‘Collaborative Robots’ or ‘Cobots’ for short. Within my project, I aim to develop robust path planning algorithms to safely and accurately operate a collaborative robot within a dynamic, human occupied workspace. Ensuring the safety of those operating within the robot workspace is paramount, therefore these algorithms will allow the robot to make real-time updates to its pre-determined path based on the constantly changing constraints of the environment. As this project is inherently multi-disciplinary, my research will be linked with projects in both the Centre for Ultrasonic Engineering and the CMAC Future Manufacturing Research Hub. 

Andre Lello

University: Imperial Supervisors: Dr Bo Lan and Professor Mike Lowe

Phd Project: Characterisation grain microstructures in metals using ultrasound

This project aims to characterise critical microstructures within engineering metals using ultrasound. Most metals are polycrystalline, and their critical performances are determined by the grain microstructures. The NDE group at Imperial College has developed a breakthrough methodology to extract volumetric texture from the speeds of compressional ultrasound. It has been validated on a conventional water-bath system, which, in addition, has produced experimental evidences that the shear waves propagating through a metal sample are strongly affected by the microstructures. The amplitudes of the shear waves correlate with the grain sizes in the propagation direction, and they vary significantly when the waves propagate in different directions in 3D, which indicates the exciting possibility to simultaneously evaluate the texture and the volumetric morphologies of the microstructures non-destructively from the same ultrasound setup. This doctorate project aims to understand the physics of the wave behaviours and develop the method for industrial application. 

Alex Towlson

University: Bristol Supervisors: Professor Anthony Croxford and Professor Bruce Drinkwater 

PhD Project: Robotic pipe inspection with ultrasonic sensor arrays

The aim of this project is to develop an ultrasonic sensor system and associated data analysis tools to extract information from the interior of a buried pipes, to detect and characterise defects such as cracks and corrosion. Such a system is required to operate in a variety of conditions, including pressurized and partially filled pipes with flow. In order to be easily deployed, it is important for the device to be compact and energy efficient, so that it can be mounted on-board an autonomous robot.