Multidimensional Tensor-Based Inductive Thermography With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection
- Submitting institution
-
University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22064176
- Type
- D - Journal article
- DOI
-
10.1109/TIE.2016.2574987
- Title of journal
- IEEE Transactions on Industrial Electronics
- Article number
- -
- First page
- 6305
- Volume
- 63
- Issue
- 10
- ISSN
- 0278-0046
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2016
- 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
-
5
- Research group(s)
-
D - Computer Vision and Natural Computing (CVNC)
- Citation count
- 69
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a multi-disciplinary research involving computational imaging, physics, and engineering. The research departs from conventional methods because it fuses multi-dimensional imaging model with physical engineering model and thermal-physics model to derive the world’s first accurate representation of the wind-turbine gear. The work has won the Most Excellent Paper Award in the 2016 IEEE International Conference on Power and Renewable Energy. The work was a major output of the EU funded project on smart condition monitoring (Grant No. 269202) which led the project judged as excellent by the expert panels.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -