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AuthorEl-Koujok, M.
AuthorBenammar, M.
AuthorMeskin, Nader
AuthorAl-Naemi, M.
AuthorLangari, R.
Available date2022-04-14T08:45:46Z
Publication Date2012
Publication NameProceedings of IEEE 2012 Prognostics and System Health Management Conference, PHM-2012
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/PHM.2012.6228969
URIhttp://hdl.handle.net/10576/29831
AbstractReliability of sensor measurement is vital to assure the performance of complex and nonlinear industrial operation. In this paper, the problem of designing and development of a data-driven multiple sensor fault detection and isolation (MSFDI) algorithm for nonlinear processes is investigated. The proposed scheme is based on an evolving multi-Takagi Sugeno framework in which each sensor output is estimated using a model derived from the available input-output measurement. Our proposed MSFDI algorithm is applied to continuously stirred tank reactor sensor fault detection and isolation. Simulation results demonstrate and validate the performance capabilities of our proposed MSFDI algorithm. 2012 IEEE.
SponsorQatar National Research Fund
Languageen
Publisher2012 3rd Annual IEEE Prognostics and System Health Management Conference, PHM-2012
SubjectContinuously stirred tank reactor
Data-driven approach
Industrial operations
Input-output
Multiple sensors
Nonlinear process
Performance capability
Sensor fault
Sensor fault detection
Sensor measurements
Sensor output
Algorithms
Systems engineering
Sensors
TitleMultiple sensor fault diagnosis for non-linear and dynamic system by evolving approach
TypeConference Paper
dc.accessType Abstract Only


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