Object structure

Title:

Dynamic neural networks for process modelling in fault detection and isolation systems

Subtitle:

.

Group publication title:

AMCS, volume 9 (1999)

Creator:

Korbicz, Józef ; Patan, Krzysztof ; Obuchowicz, Andrzej

Subject and Keywords:

fault detection ; dynamic neural networks ; non-linear modelling ; learning algorithms ; FL-classifier ; two-tank system

Abstract:

A fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points. ; To improve the quality of neural modelling, two optimization problems are included in the construction of such dynamic networks: searching for an optimal network architecture and the network training algorithm. To find a good solution, the effective well-known cascade-correlation algorithm is adapted here. ; The residuals generated by a bank of neural models are then evaluated by means of pattern classification. To illustrate the effectiveness of our approach, two applications are presented: a neural model of Narendra's system and a fault detection and identification system for the two-tank process.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Contributor:

Patton, Ronald J. - red. ; Korbicz, Józef - red.

Date:

1999

Resource Type:

artykuł

Pages:

519-546

Source:

AMCS, volume 9, number 3 (1999)

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego