Cascade network of dynamic neurons in fault detection systems

Author

Patan, K. ; Obuchowicz, A. ; Korbicz, J.

Author_Institution

Dept. of Robot. & Software Eng., Tech. Univ. of Zielona Gora, Zielona Gora, Poland

fYear

1999

fDate

Aug. 31 1999-Sept. 3 1999

Firstpage

4232

Lastpage

4237

Abstract

The cascade network of dynamic neurons (CNDN) as a neural-residual generator for fault detection in a dynamic systems is considered. The neural network is composed of dynamic neurons, which contain inner feedbacks. These neurons consists of an adder module, a linear dynamic system (IIR filter), and a non-linear activation function. The cascade-correlation algorithm is used for network architecture and parameter allocation. As a illustrative example of the diagnosed dynamic system, the two-tank system is chosen. The proposed approach is useful in neural modelling of dynamic system for FDI (Fault Detection and Isolation).

Keywords

IIR filters; cascade control; fault diagnosis; feedback; neurocontrollers; nonlinear dynamical systems; parameter estimation; CNDN; FDI; IIR filter; cascade network of dynamic neuron; cascade-correlation algorithm; fault detection and isolation; fault detection system; inner feedback; network architecture; neural network; neural-residual generator; nonlinear activation function; nonlinear dynamic system; parameter allocation; two-tank system; Pipelines; Spirals; Fault detection; dynamic neural networks; identification; nonlinear modelling;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 1999 European

Conference_Location

Karlsruhe

Print_ISBN

978-3-9524173-5-5

Type

conf

Filename

7099998