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Fault predictive diagnosis of wind turbine based on LM arithmetic of Artificial Neural Network theory

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4 Author(s)
Lincang Ju ; Sch. of Energy & Power Eng., Xi'an Jiaotong Univ., Xi'an, China ; Dekuan Song ; Beibei Shi ; Qiang Zhao

This paper analyses the main fault factors on wind turbine, and presents three general faults: gear box fault, leeway system fault and generator fault. After the analysis and research of the basic principle of Back-Propagation Neural Network based on LM arithmetic, a three-layer Back-Propagation Network faults predictive diagnosis model is built. Data from two wind turbines are used to test the effectiveness of this method.

Published in:

Natural Computation (ICNC), 2011 Seventh International Conference on  (Volume:1 )

Date of Conference:

26-28 July 2011