Sparse-TFM Imaging of Lamb Waves for the Near-Distance Defects in Plate-Like Structures

被引:14
|
作者
Zhang, Haiyan [1 ,2 ]
Liu, Yaqun [1 ,2 ]
Fan, Guopeng [1 ,2 ]
Zhang, Hui [1 ,2 ]
Zhu, Wenfa [3 ]
Zhu, Qi [4 ]
机构
[1] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200444, Peoples R China
[2] Shanghai Univ, Sch Inst Adv Commun & Data Sci, Shanghai 200444, Peoples R China
[3] Shanghai Univ Engn Sci, Sch Urban Railway Transportat, Shanghai 201620, Peoples R China
[4] Shanghai Univ, Sch Mechatron & Automat Engn, Shanghai 200444, Peoples R China
基金
中国国家自然科学基金;
关键词
Lamb waves; diffuse field; sparse-TFM algorithm; near-distance defects imaging; GREENS-FUNCTION; DIFFUSE FIELD; FULL MATRIX; ARRAYS; ALGORITHMS; EMERGENCE;
D O I
10.3390/met9050503
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The ultrasonic phased array total focusing method (TFM) has the advantages of high imaging resolution and high sensitivity to small defects. However, it has a long imaging time and cannot realize near-distance defect imaging, which limits its application for industrial detection. A sparse-TFM algorithm is adopted in this work to solve the problem regarding rapid imaging of near- distance defects in thin plates. Green's function is reconstructed through the cross-correlation of the diffuse full matrix captured by the ultrasonic phased array. The reconstructed full matrix recovers near-distance scattering information submerged by noise. A sparse array is applied to TFM for rapid imaging. In order to improve the imaging resolution, the location of active array elements in the sparse array can be optimized using the genetic algorithm (GA). Experiments are conducted on three aluminium plates with near-distance defects. The experimental results confirm that the sparse-TFM algorithm of Lamb waves can be used for near-distance defects imaging, which increases the computational efficiency by keeping the imaging accuracy. This paper provides a theoretical guidance for Lamb wave non-destructive testing of the near-distance defects in plate-like structures.
引用
收藏
页数:13
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