BP Neural Network and its Improved Algorithm in the Power System Transformer Fault Diagnosis

Hao Qian Zhang

doi:10.4028/www.scientific.net/AMM.418.200

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The Effect of Holes in the Compression Behavior and Energy Absorption of Aluminum Alloy AA7005 Tube
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BP Neural Network and its Improved Algorithm in the Power System Transformer Fault Diagnosis
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 418BP Neural Network and its Improved Algorithm in...

BP Neural Network and its Improved Algorithm in the Power System Transformer Fault Diagnosis

Abstract:

According to the measured gas content in power transformers, we use BP neural network to accomplish the pattern recognition of transformer fault. The recognition effect of BP network pattern was studied from the aspects of adding over-fitting operation and genetic algorithm. Four kinds of neural network models, BP model BP & over-fitted identification model GABP model and GABP & over-fitted identification model, were constructed respectively, making the pattern recognition effect further enhanced.

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Periodical:

Applied Mechanics and Materials (Volume 418)

Pages:

200-204

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.418.200

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Online since:

September 2013

Authors:

Hao Qian Zhang

Keywords:

BP Network, GABP Model, Over-Fitting Operation, Transformer Fault Diagnosis

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