Title: Sparse reconstruction of piezoelectric signal for phased array structural health monitoring

Authors: Yajie Sun; Feihong Gu; Sai Ji

Addresses: Jiangsu Engineering Centre of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China ' Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China

Abstract: Structural health monitoring technology has been widely used in the detection and identification of plate structure damage. Ultrasonic phased array technology has become an important method for structural health monitoring because of its flexible beam scanning and strong focusing performance. However, a large number of phased array signals will be produced, which leads to difficulty in storing, transmitting and processing. Therefore, under the condition of the signal being sparse, compressive sensing theory can make signal acquisition with much lower sampling rate than traditional Nyquist sampling theorem. Firstly, the sparse orthogonal transformation is used to make the sparse representation. Then, the measurement matrix is used for the projection observation. Besides, the reconstruction algorithm is used for sparse reconstruction. In this paper, the experimental verification of the antirust aluminium plate material is carried out. The experiment shows that the proposed method is useful for reconstructing the signal of phased array structure health monitoring.

Keywords: structural health monitoring; ultrasonic phased array; compressive sensing; matching pursuit algorithm.

DOI: 10.1504/IJHPCN.2019.102354

International Journal of High Performance Computing and Networking, 2019 Vol.14 No.4, pp.466 - 472

Received: 12 Sep 2017
Accepted: 07 May 2018

Published online: 19 Sep 2019 *

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