Self-organizing neural network for fault location in electrical circuits

Author

Osowski, Stanislaw ; Siwek, Krzysztof

Author_Institution

Inst. of Theory of Electr. Eng. & Electr. Meas., Warsaw Univ. of Technol., Poland

Volume

2

fYear

1998

fDate

1998

Firstpage

265

Abstract

A novel approach to fault location in analog dynamic circuits based on the application of self-organizing neural network has been presented. Important features are a very good generalization property and fast speed. Once the network has been trained, the recognition of the fault is done immediately, irrespective of the size of the circuit. The network is able to detect faults in the nonideal circuit, in which the tolerance of elements is taken into account. Two cases of analog circuits have been simulated and checked: the RLC circuit at multiple measurement points and the measurement done at external nodes of the circuit for multiple frequencies. The results of numerical experiments are given and discussed

Keywords

RC circuits; analogue circuits; biquadratic filters; circuit analysis computing; fault location; generalisation (artificial intelligence); ladder networks; learning (artificial intelligence); self-organising feature maps; Kohonen network; RC active biquadratic filter; RLC ladder circuit; analog dynamic circuits; computer modelling; external nodes; fault location; fault recognition; generalization property; multiple measurement points; nonideal circuit; self-organizing neural network; tolerance; Circuit faults; Electrical fault detection; Fault detection; Fault location; Frequency measurement; Intelligent networks; Neural networks; Neurons; Organizing; RLC circuits;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Circuits and Systems, 1998 IEEE International Conference on

Conference_Location

Lisboa

Print_ISBN

0-7803-5008-1

Type

conf

DOI

10.1109/ICECS.1998.814877

Filename

814877