Articles | Volume 5, issue 4
Wind Energ. Sci., 5, 1375–1397, 2020
https://doi.org/10.5194/wes-5-1375-2020

Special issue: Wind Energy Science Conference 2019

Wind Energ. Sci., 5, 1375–1397, 2020
https://doi.org/10.5194/wes-5-1375-2020

Research article 27 Oct 2020

Research article | 27 Oct 2020

Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour models

Simon Letzgus

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Simon Letzgus on behalf of the Authors (12 Aug 2020)  Author's response    Manuscript
ED: Publish as is (26 Aug 2020) by Michael Muskulus
ED: Publish as is (08 Sep 2020) by Jakob Mann(Chief Editor)
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Short summary
One of the major challenges when working with wind turbine sensor data in practice is the presence of systematic changes in signal behaviour induced by malfunctions or maintenance actions. We found that approximately every third signal is affected by such change points and introduce an algorithm which reliably detects them in a highly automated fashion. The algorithm enables the application of data-driven techniques to monitor wind turbine components using data from commonly installed sensors.