The Fault Diagnosis Based on Self-organizing Fuzzy Clustering Elman Network in Wind Turbines

被引：0

作者：

Yu, Yang ^{[1
]}

Li, Chuxin ^{[1
]}

Yang, Qing ^{[1
]}

Wang, Zilong ^{[1
]}

机构：

[1] Shenyang Ligong Univ, Sch Automat & Elect Engn, Shenyang 110159, Peoples R China

来源：

PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC) | 2016年

关键词：

Wind Turbine; Fault Diagnosis; Self-organizing Fuzzy Clustering; Elman Neural Network;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The wind turbine failure-prone transmission system (shaft, gearbox, high-speed axis and generator) were regarded as the research object in this article. A method based on self-organizing fuzzy clustering and the Elman network wind turbine faults diagnosis was proposed, which preprocessing the data samples with fuzzy clustering criterion collected by vibration sensors on wind turbine, and analysis the faults with the Elman neural network. The experimental results showed that the diagnostic accuracy of the results has been improved by the method comparing with the traditional method.

引用

页码：2940 / 2945

页数：6

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