Infrared and Laser Engineering, Volume. 51, Issue 12, 20220097(2022)
Image data compression technology of smart grid operation based on deep learning
[1] Chen W J, Zhao G L. Key technologies and equipment of new power system with new energy as the main body[J]. Global Energy Internet, 5, 1(2022).
[2] [2] Jia Y Q. Research on sequence spatial data compression technology based on deep learning[D]. Harbin: Harbin Institute of Technology, 2021. (in Chinese)
[3] Chen S W, Gao C Y, Hu C. Adaptive waveform data compression based on similarity segmentation and resampling[J]. Journal of Electronic Measurement and Instrumentation, 33, 178-185(2019).
[4] Wang Y Z, Sun L Q. Application of data compression technology in ship power monitoring system[J]. Journal of Shanghai Institute of Ship Transportation Science, 43, 55-60(2020).
[5] Unterweger A, Engel D. Resumable load data compression in smart grids[J]. IEEE Transactions on Smart Grid, 6, 919-929(2015).
[6] Chen Y, Wang Y L. Lossless data compression scheme of intelligent distribution network monitoring system[J]. Guangdong Electric Power, 34, 90-98(2021).
[7] Zhao H S, Feng J H, Ma L B. Data compression of distribution network infrared image monitoring based on tensor Tucker decomposition[J]. Power System Technology, 45, 1632-1639(2021).
[8] [8] Ye J X. Research on image acquisition reconstruction of power system based on compressed sensing[D]. Wuhan: Hubei University of Technology, 2020. (in Chinese)
[9] [9] Zhao H S, Liu B C, Wang L J, et al. Blind super resolution method f infrared images of power equipment based on compressed sensing[JOL]. Power System Technology, (20220112) [20220124]. (in Chinese)
[10] Zhao H H, Jiang Y, Lin R, et al. Research on acceleration and compression of transmission line inspection image detection model[J]. Guangdong Electric Power, 33, 123-128(2020).
[11] [11] Wang Z H. Research on compressed sensing reconstruction of electrical equipment images under the framewk of deep learning[D]. Wuhan: Hubei University of Technology, 2021. (in Chinese)
[12] Peng J S, Sun L X, Wang L, et al. ED-YOLO electric power inspection UAV obstacle avoidance target detection algorithm based on model compression[J]. Journal of Instrumentation, 42, 161-170(2021).
[13] Tang N Y, Cai L, Zhu T, et al. Construction of image recognition model for power equipment based on deep learning[J]. Automation and Instrumentation, 54-57(2020).
[14] [14] Wu Y F, Li F S, Yu T, et al. Power data compression highprecision reconstruction based on residual dual attention mechanism wk[JOL]. Power System Technology, (2022115)[20220124]. (in Chinese)
[15] Zhang S Q, Yang F B, Wang X X. Ghost imaging optimization method based on autoencoding neural network[J]. Electronic Measurement Technology, 44, 77-83(2021).
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Xin Xia, Chuanliang He, Yingjie Lv, Shouzhi Wang, Bo Zhang, Chen Chen, Haipeng Chen, Meixuan Li. Image data compression technology of smart grid operation based on deep learning[J]. Infrared and Laser Engineering, 2022, 51(12): 20220097
Category: Image processing
Received: Jan. 21, 2022
Accepted: --
Published Online: Jan. 10, 2023
The Author Email: Haipeng Chen (haipeng0704@126.com), Meixuan Li (limx@jlenu.edu.cn)