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AuthorAlizadeh E.
AuthorMeskin N.
AuthorKhorasani K.
Available date2020-04-07T11:46:18Z
Publication Date2018
Publication NameIEEE Transactions on Industrial Informatics
ResourceScopus
ISSN15513203
URIhttp://dx.doi.org/10.1109/TII.2017.2746761
URIhttp://hdl.handle.net/10576/13893
AbstractIn this paper, a fault detection and isolation (FDI) methodology based on an immune system (IS) inspired mechanism known as the dendritic cell algorithm (DCA) is developed and implemented. Our proposed DCA-based FDI methodology is then applied to a well-known wind turbine test model. The proposed DCA-based scheme performs both detection as well as isolation of sensor faults given dual sensor redundancy, unlike other works in the literature that only address the fault detection problem and rely on analytical redundancy approach for accomplishing the fault isolation task. A nonparametric statistical comparison test is also performed to compare the performance of the DCA-based FDI scheme with another IS-based scheme known as the negative selection algorithm. Through extensive simulation case study scenarios the capabilities and performance of our proposed methodologies have been fully demonstrated and justified.
Languageen
PublisherIEEE Computer Society
SubjectArtificial immune systems (AIS)
Dendritic cell algorithm (DCA)
Fault detection and isolation (FDI)
Negative selection algorithm (NSA)
Wind turbine (WT)
TitleA dendritic cell immune system inspired scheme for sensor fault detection and isolation of wind Turbines
TypeArticle
Pagination545-555
Issue Number2
Volume Number14
dc.accessType Abstract Only


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