Fault Classification of Process Layer Network in Intelligent Substation Based on ANP-SVM

doi:10.3969/j.issn.1006-2475.2019.07.013

Abstract

Abstract: Aiming at the inefficiency and data set noise of the existing process layer network fault classification in intelligent substation, this paper proposes an ANP-SVM based process layer network fault classification algorithm. Firstly, the improved separation interval method is used to optimize the selection of kernel parameters and error parameters of SVM, and then the anti-noise sample data is input into the optimized SVM, which makes the classification more accurate and efficient. The experimental results show that the algorithm has good performance in the process layer network fault classification.

Key words: intelligent substation, network failure, fault diagnosis, anti-noise processing (ANP), SVM

CLC Number:

TP391

ZHANG Kai-yan1,2, PAN Yang3, LOU Ji-chao4. Fault Classification of Process Layer Network in Intelligent Substation Based on ANP-SVM[J]. Computer and Modernization, 2019, 0(07): 72-.

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