Neuro-fuzzy identification applied to fault detection in nonlinear systems

作者:Felipe Blazquez L; de Miguel Luis J; Aller Fernando; Peran Jose R
来源:International Journal of Systems Science, 2011, 42(10): 1771-1787.
DOI:10.1080/00207721003653674

摘要

This article describes a fault detection method, based on the parity equations approach, to be applied to nonlinear systems. The input-output nonlinear model of the plant, used in the method, has been obtained by a neural fuzzy inference architecture and its learning algorithm. The proposed method is able to detect small abrupt faults, even in systems with unknown nonlinearities. This method has been applied to a real industrial pilot plant, and good performance has been obtained for the experimental case of fault detection in the level sensor of a level control process in the said industrial pilot plant.

  • 出版日期2011