Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/24711

Title: Challenges in using operational data for reliable wind turbine condition monitoring
Authors: Tautz-Weinert, Jannis
Watson, Simon J.
Keywords: Wind turbine
Condition monitoring
Machine learning
Issue Date: 2017
Publisher: © International Society of Offshore and Polar Engineers (ISOPE)
Citation: TAUTZ-WEINERT, J. and WATSON, S.J., 2017. Challenges in using operational data for reliable wind turbine condition monitoring. The Proceedings of the Twenty-seventh (2017) International Ocean and Polar Engineering Conference, San Francisco, California, USA, June 25-30 2017.
Abstract: Operational data of wind turbines recorded by the Supervisory Control And Data Acquisition (SCADA) system originally intended only for operation and performance monitoring show promise also for assessing the health of the turbines. Using these data for monitoring mechanical components, in particular the drivetrain subassembly with gearbox and bearings, has recently been investigated with multiple techniques. In this paper the advantages and drawbacks of suggested approaches as well as general challenges and limitations are discussed focusing on automated and farm-wide condition monitoring.
Description: This is a conference paper.
Sponsor: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie SklodowskaCurie grant agreement No 642108 (Advanced Wind Energy Systems Operation and Maintenance Expertise, http://awesome-h2020.eu/).
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/24711
Publisher Link: http://www.isope.org/publications/ISOPEproceedinglist.htm
ISBN: 9781880653975
ISSN: 1098-6189
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

Files associated with this item:

File Description SizeFormat
2017-TPC-0822-TautzWeinert_20170324.pdfAccepted version505.7 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.