Artificial neural networks for the modelling and fault diagnosis of technical processes

The book is mainly focused on investigating the properties of locally recurrent neural networks, developing training procedures for them and their application to the modelling and fault diagnosis of non-linear dynamic processes and plants. The material included in the monograph results from research that has been carried out at the Institute of Control and Computation Engineering of theUniversity of Zielona G´ora, Poland, for the last eight years in the area of the modelling of non-linear dynamic processes as well as fault diagnosis of industrial processes. Investigates the properties of locally recurrent neural networks, developing training procedures for them and their application to the modelling and fault diagnosis of non-linear dynamic processes and plants Includes an Introduction to fault diagnosis of non-linear systems using artificial neural networks INDICE: Introduction.- Modelling issue in fault diagnosis.- Locally recurrent neural networks.- Approximation abilities of locally recurrent networks.- Stability and stabilization of locally recurrent networks.- Optimum experimental design for locally recurrent Networks.- Decision making in fault detection.- Industrial applications.- Concluding remarks and further research directions.

• ISBN: 978-3-540-79871-2
• Editorial: Springer
• Encuadernacion: Rústica
• Páginas: 215
• Fecha Publicación: 01/07/2008
• Nº Volúmenes: 1
• Idioma: Inglés