| Resumo: | This research paper is concerned with the fault detection and isolation (FDI) problem, or more exactly, with a hierarchical structure of fuzzy neural networks (HFNN) used for fault isolation purposes in industrial processes. The main aim of this research work is to optimise the number of neurons in the hidden layer of all fuzzy neural networks (FNNs) used in the HFNN. Thus, the optimal brain surgeon (OBS) pruning algorithm has been used to prune all FNNs. After the OBS optimisation, the HFNN structure continues to be able to isolate correctly, abrupt and incipient, single and multiple faults. At the same time, the structure became simpler and better generalisation capabilities have been observed. A continuous binary distillation column having several actuated valves with PID control loops has been used as test bed of the proposed approach.
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