Intelligent Contextual Algorithm For Harmonics Classification
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CONTRIBUTORS:
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JOURNAL:
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YEAR:
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2010
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PUB TYPE:
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Journal Article
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SUBJECT(S):
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Contextual Clustering, Back Propagation Algorithm, Harmonics, Power Quality, Fast Fourier Transform.
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DISCIPLINE:
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Engineering and Applied Sciences
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HTTP:
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http://www.ijest.info/docs/IJEST10-02-06-101.pdf
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LANGUAGE:
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English
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PUB ID:
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103-489-821
(Last edited on
2011/06/24 23:06:27 GMT-6)
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SPONSOR(S):
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ABSTRACT:
This paper presents methods for classification of harmonics present in the electrical signal using Fast Fourier Transform (FFT), Contextual Clustering (CC) and Back Propagation Algorithm (BPA). Power quality meter has been used to collect the electrical signal data from a 40W Fluorescent Lamp (FL). In the captured data, various electrical disturbances are introduced through Matlab code. FFT has been used for extraction of features from the acquired electrical signal. The FFT, CC, BPA and BPACC algorithms have been implemented by Matlab. Comparison of performance classification of harmonics by CC, BPA and BPACC are presented.
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STATISTICS
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