Nonlinear system identification for model-based condition monitoring of wind turbines
- Submitting institution
-
The University of Lancaster
- Unit of assessment
- 12 - Engineering
- Output identifier
- 238286336
- Type
- D - Journal article
- DOI
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10.1016/j.renene.2014.05.035
- Title of journal
- Renewable Energy
- Article number
- -
- First page
- 166
- Volume
- 71
- Issue
- -
- ISSN
- 0960-1481
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2014
- 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
- Yes
- Number of additional authors
-
1
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research was funded by EPSRC (EP/I037326) in partnership with Wind Prospect Ltd and TNEI. The work subsequently led to collaborations on potential commercial applications with Wind Prospect and James Fisher Mimic through EPSRC IAA scheme. The JFM case study has been promoted to wider industry and public sectors by specialist publications Motorship, Ship and Bunker, and Green4Sea. As commented by JFM (Martin.Briddon@jfmimic.co.uk), the research “has helped enormously with deeper signal processing and has resulted in a deeper understanding of machinery fault situations”. The result has offered major improvements in maintenance planning for MIMIC clients and could “revolutionise fuel efficiency”.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
