The Application of Improved SVM in Mixed Circuit

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In order to improve the speed and the rate of fault diagnosis in mixed circuit, this paper introduces a new fault diagnosis method. Through extracting fault features of current characteristics effectively and applying to Improved SVM, the ability of pattern recognition will be better than the traditional BP Neural Network and Single SVM, especially in small samples or non-linear cases. Meanwhile, this paper presents the lifting wavelet transform in order to obtain the feature information accurately. The accuracy of fault diagnosis can greatly enhance by discussing the Improved SVM combined with lifting wavelet transform in a specific monostable trigger. That points out a new direction for the fault diagnosis of mixed circuit.

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Periodical:

Edited by:

Jing Guo

Pages:

493-496

Citation:

H. L. Wang et al., "The Application of Improved SVM in Mixed Circuit", Applied Mechanics and Materials, Vol. 224, pp. 493-496, 2012

Online since:

November 2012

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$38.00

[1] Zhang Qi-long, Shan Gan-lin. the fault diagnosis of analog circuit based on SVM [J]. Journal of Electricity and Control, 2010, 17(5):66~69.

[2] Vapnik V. The Nature of Statistical Learning Theory [M]. New York: Springer-Verlag, (1999).

[3] Shen Yu-hao, Meng-Chen. the fault diagnosis of simulated circuit based on Improved Support Vector Machine [J]. Computer Simulation, 2010, 27(1):346~350.

[4] C W HSU. A Comparison of Methods for Multi-class Support Vector Machines[C]. IEEE Transactions on Neural Networks, 2002, 13(2): 415~425.

[5] Zhang Jin-ze. the application of Improved Support Vector Machine in the fault diagnosis[J]. Journal of Electricity and Control, 2006, 13(6):97~100.

[6] Yang-Qing, Tian-Feng. the real-time fault diagnosis based on lifting wavelet transform and recursive LSSVM[J]. Chinese Journal of Scientific Instrument, 2011. 32(3):596~602.

[7] Wang Feng-li, Zhao De-you. the extraction of fault features based on lifting wavelet transform and local wave[J]. Chinese Journal of Scientific Instrument, 2010, 31(4):789~793.