Single atom convolutional matching pursuit: Theoretical framework and application to Lamb waves based structural health monitoring

IF 3.4 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Signal Processing Pub Date : 2025-01-18 DOI:10.1016/j.sigpro.2025.109898

Sebastian Rodriguez , Marc Rébillat , Shweta Paunikar , Pierre Margerit , Eric Monteiro , Francisco Chinesta , Nazih Mechbal

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引用次数: 0

Abstract

Lamb Waves (LW) based Structural Health Monitoring (SHM) aims to monitor the health state of thin structures. An Initial Wave Packet (IWP) is sent in the structure and interacts with boundaries, discontinuities, and with eventual damages thus generating many wave packets. An issue with LW based SHM is that at least two LW dispersive modes simultaneously exist. Matching Pursuit Method (MPM), which approximates a signal as a sum of delayed and scaled atoms taken from a known dictionary, is limited to nondispersive signals and relies on a priori known dictionary and is thus inappropriate for LW-based SHM. Single Atom Convolutional MPM, which addresses dispersion by decomposing a signal as delayed and dispersed atoms and limits the learning dictionary to only one atom, is alternatively proposed here. Its performances are demonstrated on numerical and experimental signals and it is used for damage monitoring. Beyond LW-based SHM, this method remains very general and applicable to a large class of signal processing problems.

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来源期刊

Signal Processing 工程技术-工程：电子与电气

CiteScore

9.20

自引率

9.10%

发文量

309

审稿时长

41 days

期刊介绍： Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.