Generalized Congruence Neural Networks and Application in the Fault Diagnosis of Rotary Machine

Bao Long Hu; Ji Ren Xu; Huai Hui Gao; Ji Hai Liu; Ke Ren Wang

doi:10.4028/www.scientific.net/AMM.437.535

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 437Generalized Congruence Neural Networks and...

Generalized Congruence Neural Networks and Application in the Fault Diagnosis of Rotary Machine

Abstract:

Replace power function with generalized congruence neural network and put forward a modified model and algorithm of generalized congruence neural network.Analyse structure, power function, algorithm of adjusting power and compare it with BP neural network. Compareing it with BP neural network in approaching sine function, it indicate the modified generalized congruence neural network has fast constringency speed and good stability which BP neural network has. The model and algorithm advance constringency speed and diagnosis precision.

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Periodical:

Applied Mechanics and Materials (Volume 437)

Pages:

535-539

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.437.535

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Online since:

October 2013

Authors:

Bao Long Hu*, Ji Ren Xu, Huai Hui Gao, Ji Hai Liu, Ke Ren Wang

Keywords:

BP Neural Network (BPNN), Fault Diagnosis, Generalized Congruence Neural Network, Rotary Machine

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* - Corresponding Author

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