WNN Model Based on Particle Swarm Optimization for Fault Diagnosis in Analog Circuit

Xu Sheng Gan; Hao Lin Cui; Ya Rong Wu

doi:10.4028/www.scientific.net/AMM.427-429.1048

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429WNN Model Based on Particle Swarm Optimization for...

WNN Model Based on Particle Swarm Optimization for Fault Diagnosis in Analog Circuit

Abstract:

In order to diagnose the fault in analog circuit correctly, a Wavelet Neural Network (WNN) method is proposed that uses the Particle Swarm Optimization (PSO) algorithm to optimize the network parameters. For the improvement of convergence rate in WNN based on PSO algorithm, a compressing method in research space is introduced into the traditional PSO algorithm to improve the convergence in WNN training. The simulation shows that the proposed method has a good diagnosis with fast convergence rate for the fault in analog circuit.

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Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

1048-1051

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.1048

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Online since:

September 2013

Authors:

Xu Sheng Gan*, Hao Lin Cui, Ya Rong Wu

Keywords:

Analog Circuit, Fault Diagnosis, Particle Swarm Optimization (PSO), Wavelet Neural Network

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References

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