Wavelet best basis compressed sensing of ultrasonic guided waves

TY - GEN

T1 - Wavelet best basis compressed sensing of ultrasonic guided waves

AU - Perelli, Alessandro

AU - De Marchi, Luca

AU - Flamigni, Luca

AU - Marzani, Alessandro

AU - Speciale, Nicolo

PY - 2013/3/14

Y1 - 2013/3/14

N2 - A novel Compressed Sensing (CS) procedure is presented in this study for dispersive guided wave propagation analysis in passive structure health monitoring applications. The proposed approach combines theWavelet Packet multiresolution analysis, best basis selection and coefficients thresholding to generate a sparse but accurate time-frequency representation of the acquired dispersive signal, with the CS framework to efficiently compress Lamb waves signals. This approach is tested on experimental data obtained by passive excitation in a 1 m square aluminum plate and acquiring the dispersive signal with a conventional piezoelectric sensor. The proposed algorithm performance is analysed in term of compression ratio and percent residual difference. Results show the improvement in signal reconstruction with the use of the modified CS framework respect to the EZW coding, and the robustness of the proposed approach to additive noise in transmission. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

AB - A novel Compressed Sensing (CS) procedure is presented in this study for dispersive guided wave propagation analysis in passive structure health monitoring applications. The proposed approach combines theWavelet Packet multiresolution analysis, best basis selection and coefficients thresholding to generate a sparse but accurate time-frequency representation of the acquired dispersive signal, with the CS framework to efficiently compress Lamb waves signals. This approach is tested on experimental data obtained by passive excitation in a 1 m square aluminum plate and acquiring the dispersive signal with a conventional piezoelectric sensor. The proposed algorithm performance is analysed in term of compression ratio and percent residual difference. Results show the improvement in signal reconstruction with the use of the modified CS framework respect to the EZW coding, and the robustness of the proposed approach to additive noise in transmission. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

KW - Wavelet packet analysis

KW - Best basis selection

KW - Compressed matching pursuit

KW - Ultrasonic guided waves

KW - Embedded zerotree wavelet algorithm

KW - Mother wavelet optimization

U2 - 10.1117/12.2009683

DO - 10.1117/12.2009683

M3 - Conference contribution

SN - 978-081949478-8

VL - 8695

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - Society of Photo-optical Instrumentation Engineers

T2 - SPIE 8695, Health Monitoring of Structural and Biological Systems 2013

Y2 - 11 March 2013 through 14 March 2013

ER -