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المؤلفEl-Koujok, M.
المؤلفBenammar, M.
المؤلفMeskin, Nader
المؤلفAl-Naemi, M.
المؤلفLangari, R.
تاريخ الإتاحة2022-04-14T08:45:46Z
تاريخ النشر2012
اسم المنشورProceedings of IEEE 2012 Prognostics and System Health Management Conference, PHM-2012
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/PHM.2012.6228969
معرّف المصادر الموحدhttp://hdl.handle.net/10576/29831
الملخصReliability 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.
راعي المشروعQatar National Research Fund
اللغةen
الناشر2012 3rd Annual IEEE Prognostics and System Health Management Conference, PHM-2012
الموضوعContinuously 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
العنوانMultiple sensor fault diagnosis for non-linear and dynamic system by evolving approach
النوعConference Paper


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