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Despite technological advances and progress in industrial systems, the fault diagnosis of a system remains a very important task. In fact, an effective diagnosis contributes not only to improve reliability but also to decrease in maintenance costs. This paper, presents a diagnosis approach of hybrid systems thanks to the use of Timed Automata and Neural Networks. Dynamic models (in normal and failing mode) are generated by a Timed automata based methods as well as through state equations generated by Neural Networks (NN) model.