Transient power quality disturbance denoising and detection based on improved iterative adaptive kernel regression-Reference-Cited by-同舟云学术

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Transient power quality disturbance denoising and detection based on improved iterative adaptive kernel regression

Published:2018-11-20 Issue:3 Volume:7 Page:644-657
ISSN:2196-5625
Container-title:Journal of Modern Power Systems and Clean Energy
language:en
Short-container-title:J. Mod. Power Syst. Clean Energy

Author:

WANG Yan^ORCID,LI Qunzhan,ZHOU Fulin

Funder

the National Key R&D Program of China

the Program for Application of Cophase Power Supply Technology

Publisher

Springer Science and Business Media LLC

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Link

http://link.springer.com/content/pdf/10.1007/s40565-018-0467-4.pdf

Reference27 articles.

1. Singh U, Singh SN (2017) Application of fractional Fourier transform for classification of power quality disturbances. IET Sci Meas Technol 11(1):67–76

2. Li JM, Teng ZS, Tang Q et al (2016) Detection and classification of power quality disturbances using double resolution S-transform and DAG-SVMs. IEEE Trans Instrum Meas 65(10):2302–2312

3. Wang N, Li LC, Jia QQ et al (2011) Classification of power quality disturbance signals using atomic decomposition method. Proc CSEE 31(4):51–58

4. Manikandan MS, Samantaray SR, Kamwa I (2015) Detection and classification of power quality disturbances using sparse signal decomposition on hybrid dictionaries. IEEE Trans Instrum Meas 64(1):27–38

5. Liu ZG, Zhang QG (2014) An approach to recognize the transient disturbances with spectral kurtosis. IEEE Trans Instrum Meas 63(1):46–55

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