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.
引用
收藏
页码：684 / 689
相关论文
共 50 条
  • [21] A Novel Dictionary-Based Method for Test Data Compression Using Heuristic Algorithm
    Wu, Diancheng
    Li, Jiarui
    Wang, Leiou
    Wang, Donghui
    Hao, Chengpeng
    IEICE TRANSACTIONS ON ELECTRONICS, 2016, E99C (06): : 730 - 733
  • [22] High-speed Architecture for Image Reconstruction Based on Compressive Sensing
    Chen, Yang
    Zhang, Xinmiao
    2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 1574 - 1577
  • [23] DICTIONARY-BASED RECONSTRUCTION OF THE CYCLIC AUTOCORRELATION VIA l1-MINIMIZATION FOR CYCLOSTATIONARY SPECTRUM SENSING
    Bollig, Andreas
    Mathar, Rudolf
    2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2013, : 4908 - 4912
  • [24] A dictionary-based graph-cut algorithm for MRI reconstruction
    Xu, Jiexun
    Pannetier, Nicolas
    Raj, Ashish
    NMR IN BIOMEDICINE, 2020, 33 (12)
  • [25] Dictionary-Based Sparse Reconstruction of Incomplete Relative Transfer Functions
    Koldovsky, Zbynek
    Gannot, Sharon
    29TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2021), 2021, : 1005 - 1009
  • [26] Freedom: Online Activity Recognition via Dictionary-based Sparse Representation of RFID Sensing Data
    Yao, Lina
    Sheng, Quan Z.
    Li, Xue
    Wang, Sen
    Gu, Tao
    Ruan, Wenjie
    Zou, Wan
    2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), 2015, : 1087 - 1092
  • [27] Compressive sensing of wind speed data of large-scale spatial structures with dedicated dictionary using time-shift strategy
    Wan, Hua-Ping
    Dong, Guan-Sen
    Luo, Yaozhi
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 157
  • [28] A Novel Dictionary-Based Image Reconstruction for Photoacoustic Computed Tomography
    Omidi, Parsa
    Zafar, Mohsin
    Mozaffarzadeh, Moein
    Hariri, Ali
    Haung, Xiangzhi
    Orooji, Mahdi
    Nasiriavanaki, Mohammadreza
    APPLIED SCIENCES-BASEL, 2018, 8 (09):
  • [29] Dictionary-based image reconstruction for superresolution in integrated circuit imaging
    Cilingiroglu, T. Berkin
    Uyar, Aydan
    Tuysuzoglu, Ahmet
    Karl, W. Clem
    Konrad, Janusz
    Goldberg, Bennett B.
    Uenlue, M. Selim
    OPTICS EXPRESS, 2015, 23 (11): : 15072 - 15087
  • [30] Traffic data reconstruction based on compressive sensing with neighbor regularization
    Qin, Zhenquan
    Xia, Xu
    Lu, Bingxian
    Qian, Chen
    Wang, Lei
    Lin, Chuan
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2021, 32 (06):
12345