Accelerated noncontact guided wave array imaging via sparse array data reconstruction

被引:4
|
作者
Song, Homin [1 ,2 ]
Yang, Yongchao [2 ]
机构
[1] Gachon Univ, Dept Civil & Environm Engn, 1342 Seongnamdaero, Seongnam Si 13120, Gyeonggi Do, South Korea
[2] Michigan Technol Univ, Dept Mech Engn Engn Mech, 1400 Townsend Dr, Houghton, MI 49931 USA
关键词
Guided Waves; Compressed Sensing; Noncontact Array Imaging; Scanning Laser Doppler Vibrometer; Ultrasonic Beamforming; DAMAGE DETECTION; LAMB WAVES; PHASED-ARRAYS;
D O I
10.1016/j.ultras.2021.106672
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Noncontact guided wave array imaging with a scanning laser Doppler vibrometer (SLDV) is an effective tool to detect and locate defects within a plate-like structure, as it obviates the need for installing, calibrating, and maintaining a transducer array. However, it requires collecting guided wave signals through scanning across dense spatial grid points to avoid non-defect artifacts in the array image, which is time-consuming. In this paper, we present an accelerated noncontact guided wave array imaging method that does not require dense scanning array while providing defect imaging performance comparable to the dense scanning case. In our approach, sparse scanning measurements at only a small number of points are carried out first for fast guide wave data acquisition. Then, dense guided wave array data is reconstructed from these sparse array measurements using a sparsity-promoting optimization technique, followed by delay-and-sum (DAS) beamforming to image defects within a test structure. We validate this method with laboratory experiments on composite plate specimens with multiple defects. The results demonstrate that defects within a composite plate can be successfully detected and located using sparsely sampled guided wave array measurement data. Such a significant reduction in the number of required measurement points enables accelerated noncontact guided wave array imaging.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] OPTIMIZATION OF EXPERIMENTAL PARAMETERS FOR SPARSE ARRAY IMAGING
    Hunter, A. J.
    Croxford, A. J.
    REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOLS 29A AND 29B, 2010, 1211 : 1852 - 1859
  • [32] Terahertz Imaging Based on Sparse MIMO Array
    Sun, Chao
    Chang, Qinggong
    Zhao, Rui
    Wang, Yahai
    Wang, Jinbang
    2020 INTERNATIONAL CONFERENCE ON MICROWAVE AND MILLIMETER WAVE TECHNOLOGY (ICMMT 2020 ONLINE), 2020,
  • [33] Symmetric Sparse Linear Array for Active Imaging
    Rajamaki, Robin
    Koivunen, Visa
    2018 IEEE 10TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), 2018, : 46 - 50
  • [34] Study on a Sparse Antenna Array for Terahertz Imaging
    Hu, Shaoqing
    Zhou, Min
    Chen, Xiaodong
    Alfadhl, Yasir
    2017 10TH UK-EUROPE-CHINA WORKSHOP ON MILLIMETRE WAVES AND TERAHERTZ TECHNOLOGIES (UCMMT), 2017,
  • [35] Corrosion detection and localisation utilising a novel thin film guided wave sensor sparse array
    Novosound, Glasgow, United Kingdom
    eJ. Nondestruct. Test., 2024, 6
  • [36] Enabling sparse constant propagation of array elements via Array SSA form
    Sarkar, V
    Knobe, K
    STATIC ANALYSIS, 1998, 1503 : 33 - 56
  • [37] Sparse Array Beamformer Design via ADMM
    Huang, Huiping
    So, Hing Cheung
    Zoubir, Abdelhak M.
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2023, 71 : 3357 - 3372
  • [38] Sparse Array Synthesis via Alternating Projections
    Quijano, Javier Leonardo Araque
    Vecchi, Giuseppe
    2009 IEEE ANTENNAS AND PROPAGATION SOCIETY INTERNATIONAL SYMPOSIUM AND USNC/URSI NATIONAL RADIO SCIENCE MEETING, VOLS 1-6, 2009, : 2779 - 2782
  • [39] Sparse Array Beamformer Design via ADMM
    Huang, Huiping
    So, Hing Cheung
    Zoubir, Abdelhak M.
    2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), 2022, : 336 - 340
  • [40] Sparse Array Design via Fractal Geometries
    Cohen, Regev
    Eldar, Yonina C.
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2020, 68 (4797-4812) : 4797 - 4812