| Issue |
ITM Web Conf.
Volume 11, 2017
2017 International Conference on Information Science and Technology (IST 2017)
|
|
|---|---|---|
| Article Number | 07005 | |
| Number of page(s) | 9 | |
| Section | Session VII: Control and Automation | |
| DOI | https://doi.org/10.1051/itmconf/20171107005 | |
| Published online | 23 May 2017 | |
Rule - based Fault Diagnosis Expert System for Wind Turbine
1 Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
2 School of Energy and Power Engineering, Huazhong University of Science & Technology, Wuhan 430074, China
a Corresponding author: 18140662310@163.com
Under the trend of increasing installed capacity of wind power, the intelligent fault diagnosis of wind turbine is of great significance to the safe and efficient operation of wind farms. Based on the knowledge of fault diagnosis of wind turbines, this paper builds expert system diagnostic knowledge base by using confidence production rules and expert system self-learning method. In Visual Studio 2013 platform, C # language is selected and ADO.NET technology is used to access the database. Development of Fault Diagnosis Expert System for Wind Turbine. The purpose of this paper is to realize on-line diagnosis of wind turbine fault through human-computer interaction, and to improve the diagnostic capability of the system through the continuous improvement of the knowledge base.
© Owned by the authors, published by EDP Sciences, 2017
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