Fault Diagnosis Based on Neural Network Trained by PSO Algorithm with Information Sharing Strategy for Analog Circuit

Yan Ming Wei; Xu Sheng Gan; Xue Qin Tang

doi:10.4028/www.scientific.net/AMM.687-691.3320

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Fault Diagnosis Based on Neural Network Trained by...

Fault Diagnosis Based on Neural Network Trained by PSO Algorithm with Information Sharing Strategy for Analog Circuit

Abstract:

To solve some problems in fault diagnosis for analog circuit, a neural network diagnosis method using improved PSO algorithm is proposed. For the appearance on local convergence and prematurity in the application of standard PSO algorithm, an information sharing strategy is introduced, and then improved PSO algorithm is used to train the neural network for overcoming the deficiency of BP algorithm. The simulation indicates that the proposed fault diagnosis method has the fast convergence and accuracy without local convergence and prematurity for analog circuit.

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Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

3320-3323

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.3320

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Online since:

November 2014

Authors:

Yan Ming Wei*, Xu Sheng Gan, Xue Qin Tang

Keywords:

Analog Circuit, Fault Diagnosis, Information Sharing Strategy, Neural Network, Particle Swarm Optimization (PSO)

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* - Corresponding Author

References

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