Compressive sensing with warped frequency models in lamb waves damage detection procedures

Alessandro Perelli, Tommaso Di Ianni, Luca De Marchi, Nicola Testoni, Nicolò Speciale

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Compressive Sensing (CS) has emerged as a potentially viable technique for the efficient acquisition of high-resolution signals that have a sparse representation in a fixed basis. In this work, we have developed a general approach for low rate sampling and efficient CS impulse response recovery algorithms that exploits convolution signal models of dispersive ultrasonic guided waves with a sparse representation in the frequency warped basis. We apply our framework to both to lower the sampling frequency and to enhance defect localization performances of Lamb wave inspection systems. The reconstruction algorithm is based on both the iterative support estimation and alternating minimization algorithm to further improve localization accuracy, separating the contribution of the exciting wave. As a result, an automatic detection procedure to locate defect-induced reflections was demonstrated and successfully tested on experimental Lamb waves propagating in an aluminum plate.
Original languageEnglish
Title of host publication2012 IEEE International Ultrasonics Symposium
Number of pages4
ISBN (Electronic)978-1-4673-4562-0
ISBN (Print)978-1-4673-4560-6
Publication statusPublished - 10 Oct 2012
Event2012 IEEE International Ultrasonics Symposium - Dresden, Germany
Duration: 7 Oct 201210 Oct 2012


Conference2012 IEEE International Ultrasonics Symposium


  • Dispersion
  • Acoustics
  • Compressed sensing
  • Estimation
  • Sensors
  • Convolution
  • Time-frequency analysis


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