Block-wise superposition-based frequency-domain synthetic aperture focusing imaging of leaky Rayleigh waves

Leaky Rayleigh waves can be used to detect surface or sub-surface defects. The main advantage of this type of non-contact detection method is that it is easy to realize automatic inspections. However, due to the need for waveform conversion and propagation attenuation, the echo amplitudes of leaky Rayleigh waves are small, making them highly susceptible to noise, which is not conducive to defect detection and large-area imaging. A method that combines principal component analysis (PCA) with wavelet-based hidden Markov model (WHMM) algorithms is presented to denoise leaky Rayleigh waves. Subsequently, multiple sets of denoised B-scan data are then subjected to distance amplitude curve (DAC) attenuation compensation and frequency-domain synthetic aperture focusing technique (F-SAFT) for imaging. Finally, to achieve large-area imaging, F-SAFT processed data are superimposed and stitched together using a block-wise superposition method. Compared with B-scan data stitching imaging, the proposed method has a detection time of only 1/24 of that of B-scanning while reducing the average defect size error by 21.5 %, thus effectively improving the imaging efficiency and resolution for surface defect detection.