| EPSRC Reference: |
EP/Z002567/1 |
| Title: |
Hearing Light |
| Principal Investigator: |
Mills, Dr B |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Optoelectronics Research Centre (ORC) |
| Organisation: |
University of Southampton |
| Scheme: |
Standard Research - NR1 |
| Starts: |
01 September 2024 |
Ends: |
28 February 2026 |
Value (£): |
252,818
|
| EPSRC Research Topic Classifications: |
| Instrumentation Eng. & Dev. |
Manufacturing Machine & Plant |
|
| EPSRC Industrial Sector Classifications: |
|
| Related Grants: |
|
| Panel History: |
|
|
Summary on Grant Application Form |
"Can One Hear the Shape of a Drum?" is question made famous by a 1966 article in American Mathematical Monthly. Subsequent research has confirmed that the drum shape can indeed be accurately identified exclusively from the acoustic signal, in almost all cases. In this proposal, we take this question to the extreme, and ask "Can One Hear the 3D Shape of a Crater?" except, rather than a drum that is hit, we have a crater that has just been produced through the removal of material from an incident laser pulse and the process is accompanied by an acoustic emission signature. Can we therefore read this signature to calculate the three-dimensional profile of the laser machined crater? Can we hear... light?
What we are proposing is the extremely ambitious objective of a real-time acoustic-imaging system for laser machining, where the acoustic source is the laser machining process itself. Directly imaging the sample in real-time with a camera is not possible due to the intense plasma that is generated during machining. Unlocking real-time acoustic-imaging capability through audio interrogation will unlock a new paradigm in laser materials processing, and allow real-time task optimisation, error correction, and lead to significant improvements in energy efficiency, quality control and productivity. The key ingredient is the application of deep learning for recognising these audio signatures, and the algorithms and computing hardware for this application have only just become available.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.soton.ac.uk |