Harmonic Detection Based on Genetic BP Neural Network

Abstract:

In view of the grid has a large number of harmonics, serious interference power quality, but the existing harmonic detection has many disadvantages, this paper uses genetic algorithm to optimize the BP neural network (GA-BP),Combined with fanaticism, independent component technique in the separation technology, achieve rapid separation and accurate fitting for harmonic reduction. The method to solve the problem of slow convergence speed of BP neural network and easier to fall into local optimal solution; Separation, independent component analysis in the signal could not accurate reduction the source signal. In this paper a signal containing harmonic component are simulated. Results show that GA-BP neural network optimization independent component analysis has convergence speed, high precision, compared with the single BP neural network and the independent component analysis of the superiority.

• Periodical: Applied Mechanics and Materials (Volumes 427-429)
• Pages: 1892-1895
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.427-429.1892
• Online since: September 2013
• Authors: Peng Fei Song*, Jian Sheng Zhang, Yong Hua Zhang
• Keywords: GA-BP Neural Network, Harmonic, Independent Component

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