Compressed Sensing to Power Quality Signal with Orthogonal Matching Pursuit Method

DOI

10.2991/icmmita-16.2016.12How to use a DOI?

Keywords

Compressed sensing; Power quality; Sparse representation; Orthogonal matching pursuit

Abstract

Compressed sensing is a new data compression method which can recover a sparse or compressible signal from a small number of linear and non-adaptive measurements. To solve the problems of high sampling rate and massive data storage faced by traditional collection and compression methods of power quality, compressed sensing algorithm is used in the paper. Gaussian random measurement matrix is used to complete the compressed sampling. The orthogonal matching pursuit method is adopted in the reconstruction processes. Simulation show that The SNR of the reconstruction of harmonics signal using compressed sensing is higher than the traditional compression method such as wavelet transform and DCT transform.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Hua Ouyang
AU  - Zhonglin Yang
AU  - Hui Li
PY  - 2017/01
DA  - 2017/01
TI  - Compressed Sensing to Power Quality Signal with Orthogonal Matching Pursuit Method
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 60
EP  - 63
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.12
DO  - 10.2991/icmmita-16.2016.12
ID  - Ouyang2017/01
ER  -