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Neural network approach of harmonics detection

Authors: Zin, A.A.M; Rokonuzzaman, M.; Shaibon, H.; Lo, K.I.;

Neural network approach of harmonics detection

Abstract

This paper describes a novel approach of harmonics detection in a power system which can be used as an alternative to the conventional approaches. The proposed approach uses the multilayer feed forward neural network to determine the harmonic components in a six-pulse bridge converter. In this paper the detection of 5th, 7th, and 11th harmonic components from the distorted waves has been verified by means of the computer simulation. It is found that once trained by the learning algorithm, the neural network can determine each harmonic component very effectively and efficiently.

Country
Malaysia
Keywords

TK Electrical engineering. Electronics Nuclear engineering

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Top 10%
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