Study of Fault Transient Detection Method Based on Chaotic Neural Network

Shang Yuang Li

doi:10.4028/www.scientific.net/AMR.662.740

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 662Study of Fault Transient Detection Method Based on...

Study of Fault Transient Detection Method Based on Chaotic Neural Network

Abstract:

In order to make the best of abundant fault transient information, a neural network fault detecting method based on transient information is proposed. Firstly, a appropriate orthogonal wavelets packet function is chosen in order to effectively distill fault transient information; and then a chaotic neural network is employed to detect SPGFs, by which the interference of false and non- fault transient information is overcome, its weight coefficient and parameters are optimized by improved genetic algorithm; Finally, a numerical type of fault detecting criterion is designed. Effectiveness and advantage of the proposed method is tested by several experiments.

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Periodical:

Advanced Materials Research (Volume 662)

Pages:

740-745

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.662.740

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Online since:

February 2013

Authors:

Shang Yuang Li

Keywords:

Chaotic Neural Network, Genetic Algorithm (GA), Transient Information, Wavelets Packet

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References

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