Harmonic detection algorithm based on improved SVD and Prony
An improved algorithm based on singular value decomposition(SVD) and Prony is proposed to solve the problem that the traditional Prony algorithm is not very accurate because it is sensitive to noise during harmonic and inter-harmonic detection. Based on SVD theory, a singular point auxiliary algorit...
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National Computer System Engineering Research Institute of China
2019-01-01
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doaj-db00c22d3b6d40af9b96d4ef30c69a7a2020-11-25T01:08:08ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982019-01-01451465010.16157/j.issn.0258-7998.1827873000096357Harmonic detection algorithm based on improved SVD and PronyYing Jun0Zhu Yunpeng1He Chao2School of Optoelectronic Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,ChinaSchool of Optoelectronic Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,ChinaKey Laboratory of Optical Communication and Networks,Chongqing University of Posts and Telecommunications, Chongqing 400065,ChinaAn improved algorithm based on singular value decomposition(SVD) and Prony is proposed to solve the problem that the traditional Prony algorithm is not very accurate because it is sensitive to noise during harmonic and inter-harmonic detection. Based on SVD theory, a singular point auxiliary algorithm is proposed to select the effective order of singular value decomposition adaptively, so as to accurately filter out the noise signal. According to the exact effective order, the improved Prony algorithm is used to identify the parameters of the signal after noise elimination, and the parameters of each harmonic and its components can be estimated accurately. Through MATLAB simulation analysis, it is shown that the algorithm can accurately extract the parameter information of power signal and has certain application value.http://www.chinaaet.com/article/3000096357harmonic detectionsingular value decompositionsingular point detectionProny |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
author |
Ying Jun Zhu Yunpeng He Chao |
spellingShingle |
Ying Jun Zhu Yunpeng He Chao Harmonic detection algorithm based on improved SVD and Prony Dianzi Jishu Yingyong harmonic detection singular value decomposition singular point detection Prony |
author_facet |
Ying Jun Zhu Yunpeng He Chao |
author_sort |
Ying Jun |
title |
Harmonic detection algorithm based on improved SVD and Prony |
title_short |
Harmonic detection algorithm based on improved SVD and Prony |
title_full |
Harmonic detection algorithm based on improved SVD and Prony |
title_fullStr |
Harmonic detection algorithm based on improved SVD and Prony |
title_full_unstemmed |
Harmonic detection algorithm based on improved SVD and Prony |
title_sort |
harmonic detection algorithm based on improved svd and prony |
publisher |
National Computer System Engineering Research Institute of China |
series |
Dianzi Jishu Yingyong |
issn |
0258-7998 |
publishDate |
2019-01-01 |
description |
An improved algorithm based on singular value decomposition(SVD) and Prony is proposed to solve the problem that the traditional Prony algorithm is not very accurate because it is sensitive to noise during harmonic and inter-harmonic detection. Based on SVD theory, a singular point auxiliary algorithm is proposed to select the effective order of singular value decomposition adaptively, so as to accurately filter out the noise signal. According to the exact effective order, the improved Prony algorithm is used to identify the parameters of the signal after noise elimination, and the parameters of each harmonic and its components can be estimated accurately. Through MATLAB simulation analysis, it is shown that the algorithm can accurately extract the parameter information of power signal and has certain application value. |
topic |
harmonic detection singular value decomposition singular point detection Prony |
url |
http://www.chinaaet.com/article/3000096357 |
work_keys_str_mv |
AT yingjun harmonicdetectionalgorithmbasedonimprovedsvdandprony AT zhuyunpeng harmonicdetectionalgorithmbasedonimprovedsvdandprony AT hechao harmonicdetectionalgorithmbasedonimprovedsvdandprony |
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1725184077930168320 |