Project Outline
Linking impact sound to performance, impact mechanics in cricket, tennis, and golf.
Cricket players recognise the sound of a sweetly struck shot straight away, and golfers know which impact sounds signal a clean strike. Athletes use these cues to judge how well the ball was hit, and how fast it is travelling, before they see the result. What is still missing is the science: we do not yet know how much of that information is really carried in the sound, or how to measure it. This PhD aims at finding this out.
If a simple microphone can tell you where on the bat contact occurred and how cleanly the ball was struck, then performance feedback that today needs expensive camera systems could reach players at every level.
Further project information
Core question: how do the acoustic signatures of ball and implement impacts relate to impact location on the element, contact quality, timing and the resulting ball trajectory, and how much of that information survives in a realistic recording?
You will approach this by combining three strands. First, physics based modelling of the implement and ball: structural dynamics, contact mechanics and sound radiation, to understand how bat or racket flexibility and ball properties shape the radiated sound. Second, measurement: controlled laboratory experiments at ISVR alongside audio recorded in real play. Third, data analysis: signal processing and physics informed machine learning to identify the acoustic features that carry performance information, including microphone array methods for locating impact events in space.
The work starts with cricket, where the bat and ball dynamics are best understood, and extends to tennis, and golf to test how far the acoustic indicators generalise across sports.
Subject Areas
- Acoustics;
- Vibration and structural dynamics;
- Sports engineering and sports technology;
- Signal processing;
- Machine learning and AI;
- Mechanical engineering;
- Applied physics.
Required technical skills/academic qualifications/experience
A minimum 2:1 undergraduate or masters degree (or international equivalent) in engineering, physics, mathematics, computer science or a related scientific subject.
You must have a good understanding of physics and mathematics, and some programming experience in any language, for example Python or MATLAB.
During the PhD you will develop skills in acoustics, structural dynamics and vibration, experimental measurement, signal processing and machine learning. Training is available through taught modules at ISVR and through the CDT programme, so you do not need experience of every technique described above to apply.
We value curiosity, persistence, collaboration and a willingness to learn. We are committed to building a diverse research community and particularly welcome applications from women and other groups under-represented in acoustics research. All appointments are made on merit.
If the topic interests you but you are unsure whether you meet every requirement, we encourage you to apply.
Mode of attendance
Successful applicants are expected to register as full-time students. However, eligible UK home fees applicants may request to be considered for part-time attendance by the supervisory team.
Supervisors
Project Partners
This project will be hosted at the University of Southampton with support from Hawk-Eye Innovations Ltd
