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Khosravi, Abbas
Armengol Llobet, Joaquim Gelso, Esteban Reinaldo |
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| Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately | |
| http://hdl.handle.net/2072/66789 | |
| eng | |
| IEEE | |
| Tots els drets reservats | |
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Anà lisi d’intervals (Matemà tica)
Control automà tic Errors de diagnòstic Sistemes dinà mics diferenciables Automatic control Differentiable dynamical systems Diagnostic errors Interval analysis (Mathematics) |
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| An Interval Intelligent-based Approach for Fault Detection and Modelling | |
| info:eu-repo/semantics/article | |
| Recercat |
