Thursday, 29 September 2016
11:30 - 13:00 Component reliability and diagnostics: early detection and intervention is key!
O&M & logistics  
          

This session will give an insight into wind turbine reliability and the state of the art in wind turbine diagnostics. It will look at how to collect and analyse reliability data in order to improve design as well as O&M strategies. This session will also look at the use of supervisory control and data acquisition (SCADA) data for condition monitoring: both 'conventional' ten minute data and higher frequency 1Hz data. Finally, there will be a case study of how power data from the converter can be used to infer wind turbine loading.

You attended this session?

Please give us feedback

 

Co-chair(s):

Abstract ID: 134 science & research
Christopher Smith
Postgraduate Researcher, Durham University, United Kingdom
Monitoring wind turbine loading using power converter signals

Abstract ID: 161
Berthold Hahn
Head of Department, Fraunhofer IWES, Germany
Recommended practices for data collection, reliability assessment and O&M optimisation

Abstract ID: 229 science & research
Stefan Faulstich
Group Manager, Fraunhofer IWES, Germany
Modelling the failure behaviour of wind turbines

Abstract ID: 336
Elizabeth Traiger
Senior Researcher, DNV GL, United Kingdom
Give it all you got: using big data machine learning ensembles for condition monitoring

Abstract ID: 361
Henrik Pedersen
Manager, Siemens Wind Power A/S, Denmark
Reduce production loss through early-stage detection of abnormal behaviour