Fault Diagnosis of Wind Turbine's Converter Based on Memristive Neural Network

Yun Liang Wang; Xun Wang

doi:10.4028/www.scientific.net/AMM.705.333

Paper Titles

Research on Correction to Fitting Factors of Shape Function and Convergence of Wind Turbine Airfoils
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Effect of Anti-Reflective Layer in Dye-Sensitized Solar Cells
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Analysis of Research Trends of Organic Solar Cell Using Patent Information
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Research on the Application of Fuel Cell in the Electricity-Generating Industry
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Fault Diagnosis of Wind Turbine's Converter Based on Memristive Neural Network
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Speed Sensorless Control with ANN-MRAS Based on Modified ACO for Induction Motor Drives
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Distributed Cross-Direction Control System Based on CAN-Bus
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Design and Application of Hotel Intelligent Control System
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A Novel Traction Control Strategy Based on Optimal Slip Ratio Control for Electric Vehicle
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 705Fault Diagnosis of Wind Turbine's Converter Based...

Fault Diagnosis of Wind Turbine's Converter Based on Memristive Neural Network

Abstract:

In this paper, a memristive neural network was applied to fault diagnosis of wind turbine's converter. A model of memristive neural network was built in order to diagnose and analyze of the failure information by MATLAB Simulink. Experimental results show that the proposed method can achieve better results and has certain significance for the application of memristors widely used in the near future.

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Periodical:

Applied Mechanics and Materials (Volume 705)

Pages:

333-337

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.705.333

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Online since:

December 2014

Authors:

Yun Liang Wang*, Xun Wang

Keywords:

Converter, Fault Diagnosis, Memristor, Neural Network, Wind Power

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* - Corresponding Author

References

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