Online wind turbine fault detection through automated SCADA data analysis

364 indexed citations

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This paper, published in 2009, received 364 indexed citations. Written by A. Zaher, S.D.J. McArthur, David Infield and Yash Patel covering the research area of Management Science and Operations Research, Artificial Intelligence and Political Science and International Relations. It is primarily cited by scholars working on Control and Systems Engineering (299 citations), Electrical and Electronic Engineering (128 citations) and Civil and Structural Engineering (73 citations). Published in Wind Energy.

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Countries where authors are citing Online wind turbine fault detection through automated SCADA data analysis

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This map shows the geographic impact of Online wind turbine fault detection through automated SCADA data analysis. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Online wind turbine fault detection through automated SCADA data analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Online wind turbine fault detection through automated SCADA data analysis more than expected).

Fields of papers citing Online wind turbine fault detection through automated SCADA data analysis

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Online wind turbine fault detection through automated SCADA data analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Online wind turbine fault detection through automated SCADA data analysis.

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This paper is also available at doi.org/10.1002/we.319.

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