Wind turbine pitch faults prognosis using a-priori knowledge-based ANFIS-Reference-Cited by-同舟云学术

Wind turbine pitch faults prognosis using a-priori knowledge-based ANFIS

Published:2013-12 Issue:17 Volume:40 Page:6863-6876
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Chen Bindi,Matthews Peter C.,Tavner Peter J.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference26 articles.

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2. Chen, B., Qiu, Y., Feng, Y., Tavner, P., & Song, W. (2011). Wind turbine SCADA alarm pattern recognition. In IET conference on renewable power generation (RPG 2011), Edinburgh, IET.

3. Bayesian networks for wind turbine fault diagnosis;Chen,2012

4. EWEA. (2011). Wind in power. Retrieved 8 Aug, 2012, from http://www.ewea.org/fileadmin/ewea_documents/documents/publications/statistics/Stats_2011.pdf.

5. Use of SCADA and CMS signals for failure detection and diagnosis of a wind turbine gearbox;Feng,2011

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