Ultrasonic phased array signal compressed sensing in defect detection

A Compressed Sensing(CS)based procedure specifically dedicated to phased array signals and images in ultrasonic nondestructive detection is proposed,aiming to reduce a huge amount of data collection,storage,and in some instances data transmission.First of all,five greedy algorithms were employed to reconstruct simulated signals.The optimal one was selected according to the percent residual difference,and the impact of noise level was also considered.An excellent image recovery was reached using measurement points less than the Nyquist sampling limitation required.The experimental verification was presented on echo signals reflected from artificial defects.Through a quantitative sparsity calculation,the most suitable sparse basis was chosen,and the reconstruction performance was further improved via five sensing matrices selection.Although not as impressive as the simulated results,CS algorithm verified its efficiency and practicability in ultrasonic array image reconstruction using a small amount of samples,with defects fully recognizable.In addition,both in simulation and experiment,we studied the influence of Sampling Rate(SR),keeping the measurement points same.The results imply that,when measurement points increase to some extent,CS is independent with SR.