A Wavelet Dictionary-Based Compressive Sensing Method for Reconstruction of Wind Speed Data

被引：0
|
作者：
Zhu, Yikai [1 ,2 ]
Yu, Zhefan [1 ,2 ]
Chen, Anni [1 ,2 ]
Wan, Huaping [1 ,2 ]
机构：
[1] Key Laboratory of Concrete and Pre-stressed Concrete Structures of Ministry of Education, Southeast University, Nanjing,211189, China
[2] College of Civil Engineering and Architecture, Zhejiang University, Hangzhou,310058, China
来源：
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | 2024年 / 44卷 / 04期
关键词：
Signal reconstruction - Wind effects - Wind speed;
D O I：
10.16450/j.cnki.issn.1004-6801.2024.04.008
中图分类号：
学科分类号：
摘要：
Wind speed is usually non-stationary and not naturally sparse. The commonly used dictionary for the compressed sensing（CS）method is not effective for the reconstruction of the wind speed signals. In this paper，the wavelet dictionary is introduced to improve the sparsity of wind speed signals and effectively enhance the ac- curacy of the reconstructed signal. The effectiveness of this method is verified using both wind speed simulation data and monitored wind speed data of Canton Tower. The effects of data missing scenarios，regularization pa- rameters，wavelet dictionary layers，and wavelet types on the reconstruction performance of the CS method are explored in detail. The results show that the wavelet dictionary-based CS method has high accuracy in recon- structing the missing wind speed signals. © 2024 Nanjing University of Aeronautics an Astronautics. All rights reserved.
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页码：684 / 689
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