Adaptive Neuro-Fuzzy inference system for mid term prognostic error stabilization.

Otilia Dragomir (1) , Rafael Gouriveau (1) , Noureddine Zerhouni (1)

1 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

The high costs in maintaining complex equipments make necessary to enhance maitenance support systems and industrial and research communities take a growing interest in the "prognostic process". However, this activity is still not well bounded and real prognostic systems are scarce. Thus, the general purpose of the paper is to explore the way of performing failure prognostics so that manager can act consequently. The prognostic process is discussed from different points of view (concept, metrics, approaches and tools) in order to point out the pragmatic challenges of this activity. Assuming that maintenance decisions follow from a prediction step, the stabilization of mid term prediction errors appears to be essential. For that purpose a neuro-fuzzy predictor based on the ANFIS model is proposed to perform prognostic.

Mots clés: error of prediction; Prognostic; neuro-fuzzy system; ANFIS; error of prediction.

Domaines: Automatique / Robotique

Otilia Dragomir, Rafael Gouriveau, Noureddine Zerhouni. Adaptive Neuro-Fuzzy inference system for mid term prognostic error stabilization.. International Conference on Computers, Communications & Control, ICCCC'08., May 2008, Baile Felix, Oradea, Romania. pp.271-276. ⟨hal-00280924⟩