吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 675-680.doi: 10.13229/j.cnki.jdxbgxb201502051

• Orignal Article • Previous Articles    

PSO based feature extraction method for analog circuit fault information

LIU Hong1,SUN Shuang-zi2,WANG Qing-yuan1,LI Yan-zhong1   

  1. 1.School of Photo-Electronic Engineering,Changchun University of Science and Technology,Changchun 130022,China;
    2.School of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022,China
  • Received:2013-12-13 Online:2015-04-01 Published:2015-04-01

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Abstract: In order to improve the diagnosis efficiency of faulty circuits with tolerance and to ameliorate the characteristic description of faulty symptom, first, the faulty features of the circuit with tolerance are created by information entropy method. Then, a feature extraction method based on discrete Particle Swarm Optimization (PSO) algorithm is proposed to obtain the optimal feature subset of the faulty features. Finally, the optimal feature subset is used to train the classifier to diagnose the faults of circuit with tolerance. Experiment results validate this proposed method.

Key words: information process technique, information entropy, particle swarm optimization, feature extraction, analog circuits, fault location

CLC Number: 

  • TN707
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