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A Parameterization Power Data Compress Using Strong Trace Filter and Dynamics

delete2015-10-01
delete10
PRE
AI
何
何顺帆 (Shunfan He) *
M
Ming Zhang
田
田威 (Wei Tian)
J
Junmin Zhang
丁
丁凤 (Feng Ding)
DOI:10.1109/TIM.2015.2416451delete
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Abstract

Abstract

En 中文
This paper proposed a parameterization power data compress using strong trace filter (STF) and dynamics (Dyn). The STF estimates the fundamental and harmonic component parameters. When there are only fundamental and harmonic components, the power data frame is compressed in parameter form. When there are other disturbances, the fading factors of STF and Dyn are used to recognize possible transient disturbances and interharmonics, respectively. By subtracting the fundamental and harmonic components, the residue of disturbances is coded by lifting wavelet transform (LWT). Then, the estimated parameters and LWT coefficients are used to reconstruct the power signal. The proposed method places emphasis on two important steps of parameterization power data compress and has a better performance than that of the related methods when the compress ratio is the same.
Keywords:
Data compress
disturbance detection
dynamics (Dyn)
power quality
strong trace filter (STF)
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Journal

IEEE Transactions on Instrumentation and Measurement cover
IEEE Transactions on Instrumentation and Measurement
IF:
5.9
Papers:
2.0W
Citations:
5.8W

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W
wuhan textile university
Scholars:
6.7K
Papers: 4.0K
Citations: 3
South Central Minzu University cover
South Central Minzu University
Scholars:
4.6K
Papers: 3.3K
Citations: 3.4K
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