Analysing RMS and peak values of vibration signals for condition monitoring of wind turbine gearboxes
- Submitting institution
-
University of Bristol
- Unit of assessment
- 12 - Engineering
- Output identifier
- 90340126
- Type
- D - Journal article
- DOI
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10.1016/j.renene.2016.01.006
- Title of journal
- Renewable Energy
- Article number
- -
- First page
- 90
- Volume
- 91
- Issue
- -
- ISSN
- 0960-1481
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- 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
-
3
- Research group(s)
-
F - Robotics
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This pioneering work founded by EPSRC (Grant EP/G037353/1) is the first paper describing predictive maintenance techniques for early detection of failures in wind turbine gearboxes (WTs), proving a benchmark tool for offshore wind farms owners to make decision in advance to plan and schedule for operations and maintenance to reduce cost. Techniques were validated using data from 10WTs and implemented by sponsored company Vestas to up-tower repair on all sites, leading to annual cost savings of €5-10 million in service costs for Vestas and its customers. Included in IDC impact Case Study report 2017.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -