scholarly journals Fault Detection and Classification in Power Electronic Circuits Using Wavelet Transform and Neural Network

2011 ◽  
Vol 7 (1) ◽  
pp. 95-100 ◽  
Author(s):  
Prasannamoorthy
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Fault Detection ◽  
Power Electronic ◽  
Electronic Circuits ◽  
Fault Detection And Classification ◽  
Power Electronic Circuits

Research on Fault Prediction Method of Power Electronic Circuits Based on Particle Swarm Optimization RBF Neural Network

2014 ◽  
Vol 687-691 ◽  
pp. 3354-3360 ◽  
Author(s):  
Shen Yu Wang ◽  
Dan Jiang Chen ◽  
Yin Zhong Ye
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Rbf Neural Network ◽  
Particle Swarm ◽  
Fault Prediction ◽  
Power Electronic ◽  
Electronic Circuits ◽  
Characteristic Parameters ◽  
Swarm Optimization ◽  
Power Electronic Circuits

Aiming at the issue of fault prediction technique of power electronic circuits, a method based on characteristic parameter data and Particle Swarm Optimization RBF(Radial Basis Function) Neural Network for the fault prediction of power electronic circuits was proposed. Taking the Buck converter circuit as an example,the fault prediction of power electronic circuits was achieved. Firstly,the output voltage was selected as monitoring signal, then the average voltage and ripple voltage were extracted as characteristic parameters. Lastly Particle Swarm Optimization RBF Neural Network was used to predict the fault. The experimental results show that the Particle Swarm Optimization RBF Neural Network is more accurate in predicting than the only RBF Neural Network.The new method can trace the characteristic parameters’ trend and can be effectively applied in fault prediction of power electronic circuits.

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