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Showing 1 results for Incipient Fault Trend Prediction
Hossein Safaeipour, Mehdi Forouzanfar, Amin Ramezani, Volume 8, Issue 1 (9-2021)
Abstract
In chemical processes, thermal reactors are described by nonlinear closed-loop dynamic models. Timely detection of simultaneous fouling phenomena in the heat transfer system is a concern of this art. In this work, a new incipient fault diagnosis approach is proposed for application in the closed-loop non-isothermal continuous stirred-tank reactor (CSTR) system subjected to simultaneous Gaussian and non-Gaussian noises. First, the state vector is estimated by applying the well-known particle filter estimator. Then, the primary residual signal is generated using the system measurements, and the fault vector estimation is obtained. After that, by an adaptive either fixed threshold design applied in the online monitoring devised with the proposed evaluation technique, while the fault detectability is improved, the false detection problem is restricted to the system permitted number. Bank on, preventive maintenance scheduling also incipient fault trend prediction have become possible using the Gauss-Newton identification method. Finally, in order to evaluate the proposed approach, the simultaneous fouling incipient fault diagnosis over the heat transfer unit built-in nonlinear closed-loop CSTR system is considered. Furthermore, the confusion matrix and associated evaluation indices are employed to assess the simulation results quantitatively.
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نشریه سامانههای غیرخطی در مهندسی برق در خصوص اصول اخلاقی انتشار مقاله، از توصیههای «کمیته بینالمللی اخلاق نشر» موسوم به COPE و «منشور و موازین اخلاق پژوهش» مصوب معاونت پژوهش و فناوری وزارت علوم، تحقیقات و فناوری تبعیت میکند. |
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