A probabilistic compressive sensing framework with applications to ultrasound signal processing
- Submitting institution
-
The University of Sheffield
- Unit of assessment
- 12 - Engineering
- Output identifier
- 5704
- Type
- D - Journal article
- DOI
-
10.1016/j.ymssp.2018.07.036
- Title of journal
- Mechanical Systems and Signal Processing
- Article number
- -
- First page
- 383
- Volume
- 117
- Issue
- -
- ISSN
- 0888-3270
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is the first to introduce compressive sensing (CS) for NDT robotic inspection. The paper demonstrates (via a composite aerospace structure) the potential to significantly speed up inspection of safety critical parts post manufacture. A computationally efficient probabilistic approach to CS is developed, allowing proper handling of uncertainty and avoiding the need to tune the sparsity level in an ad-hoc manner. This is the key finding of the EPSRC project EP/N018427/1, and is expected to have a large industrial impact. It also forms the critical element in a multi-institutional EPSRC grant proposal 'Augmented Inspection in Manufacturing' currently under review.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -