PSO Based Feature Extraction Method for Analog Circuits Fault Information

Hong Liu; Shuang Zi Sun

doi:10.4028/www.scientific.net/AMM.721.509

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 721PSO Based Feature Extraction Method for Analog...

PSO Based Feature Extraction Method for Analog Circuits Fault Information

Abstract:

In order to improve the diagnosis efficiency of faulty circuits with tolerance and to ameliorate characteristic description of faulty symptom, the faulty features of the circuit with tolerance are created by information entropy method at first, and then feature extraction method based on discrete Particle Swarm Optimization algorithm (PSO) is proposed to obtain the optimal feature subset of faulty feature. At last, the optimal feature subset is used to train the classifier to diagnosis the faults of the circuit with tolerance. Experiments results show the validity of this proposed method.

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Periodical:

Applied Mechanics and Materials (Volume 721)

Pages:

509-512

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.721.509

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Online since:

December 2014

Authors:

Hong Liu*, Shuang Zi Sun

Keywords:

Analog Circuits, Fault Location, Feature Extraction, Information Entropy, Information Process Technique, Particle Swarm Optimization (PSO)

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* - Corresponding Author

References

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