Application of ENN-1 for Fault Diagnosis of Wind Power Systems
Joint Authors
Wang, Meng-Hui
Chen, Hung-Cheng
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-07-15
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Maintaining a wind turbine and ensuring secure is not easy because of long-term exposure to the environment and high installation locations.
Wind turbines need fully functional condition-monitoring and fault diagnosis systems that prevent accidents and reduce maintenance costs.
This paper presents a simulator design for fault diagnosis of wind power systems and further proposes some fault diagnosis technologies such as signal analysis, feature selecting, and diagnosis methods.
First, this paper uses a wind power simulator to produce fault conditions and features from the monitoring sensors.
Then an extension neural network type-1- (ENN-1-) based method is proposed to develop the core of the fault diagnosis system.
The proposed system will benefit the development of real fault diagnosis systems with testing models that demonstrate satisfactory results.
American Psychological Association (APA)
Wang, Meng-Hui& Chen, Hung-Cheng. 2012. Application of ENN-1 for Fault Diagnosis of Wind Power Systems. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1001401
Modern Language Association (MLA)
Wang, Meng-Hui& Chen, Hung-Cheng. Application of ENN-1 for Fault Diagnosis of Wind Power Systems. Mathematical Problems in Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-1001401
American Medical Association (AMA)
Wang, Meng-Hui& Chen, Hung-Cheng. Application of ENN-1 for Fault Diagnosis of Wind Power Systems. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1001401
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1001401