Show simple item record

AuthorAlizadeh, Esmaeil
AuthorMeskin, Nader
AuthorKhorasani, Khashayar
Available date2020-09-24T08:11:56Z
Publication Date2017
Publication NameIEEE Transactions on Cybernetics
ResourceScopus
ISSN21682267
URIhttp://dx.doi.org/10.1109/TCYB.2016.2582384
URIhttp://hdl.handle.net/10576/16278
AbstractHigh operational and maintenance costs represent as major economic constraints in the wind turbine (WT) industry. These concerns have made investigation into fault diagnosis of WT systems an extremely important and active area of research. In this paper, an immune system (IS) inspired methodology for performing fault detection and isolation (FDI) of a WT system is proposed and developed. The proposed scheme is based on a self nonself discrimination paradigm of a biological IS. Specifically, the negative selection mechanism [negative selection algorithm (NSA)] of the human body is utilized. In this paper, a hierarchical bank of NSAs are designed to detect and isolate both individual as well as simultaneously occurring faults common to the WTs. A smoothing moving window filter is then utilized to further improve the reliability and performance of the FDI scheme. Moreover, the performance of our proposed scheme is compared with another state-of-the-art data-driven technique, namely the support vector machines (SVMs) to demonstrate and illustrate the superiority and advantages of our proposed NSA-based FDI scheme. Finally, a nonparametric statistical comparison test is implemented to evaluate our proposed methodology with that of the SVM under various fault severities. 1 2013 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectArtificial immune system (AIS)
fault detection and isolation (FDI)
negative selection algorithm (NSA)
support vector machines (SVMs)
wind turbines (WTs)
TitleA Negative Selection Immune System Inspired Methodology for Fault Diagnosis of Wind Turbines
TypeArticle
Pagination3799-3813
Issue Number11
Volume Number47
dc.accessType Abstract Only


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record