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2 International Journal of Applied Mathematics and Computer Science

2 1999

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Development of Dynamic Neural Networks With Application to Observer-Based Fault Detection and Izolation

Marcu T., Mirea L., Frank P. M.

International Journal of Applied Mathematics and Computer Science

1999

Vol. 9, no 3

547-570

The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The main emphasis is placed upon the development of neural observer schemes. They are built based on dynamic neural networks, i.e. dynamic multi-layer perceptrons with mixed structure. The goal is to achieve an adequate approximation of process outputs for known classes of the process behaviour. The obtained symptoms are then classified by means of static artificial nets. Appropriate decision mechanisms are designed for each type of observer schemes. An application to a laboratory process is included. It refers to component and instrument fault detection and isolation in a three-tank system.

Application of Sensitivity Theory to Fuzzy Logic Based Fdi

Dalton T., Klotzek P., Frank P. M.

International Journal of Applied Mathematics and Computer Science

1999

Vol. 9, no 3

619-636

This paper describes an application of sensitivity theory to the analysis of a certain class of fuzzy systems which can be used for fault detection and isolation (FDI). The work is divided into three main tasks. The first is the mathematical representation of some class of fuzzy systems. This is followed by an application of sensitivity theory to fuzzy systems based on the approach detailed in the first part. Finally, this method is applied to a fuzzy fault diagnosis scheme for the two-tank system, and the results compared with those achieved by the application of sensitivity theory to a non-fuzzy diagnosis scheme for the same system. Simulation results for the fuzzy and non-fuzzy fault diagnosis schemes are presented, which verify the results obtained via the application of sensitivity theory.