Abstract:Ultrasonic leaky Rayleigh waves can be used to detect surface and sub-surface defects. The advantage of non-contact detection makes it easy to realize automatic inspection. However, due to the waveform conversion and propagation attenuation, the echo amplitude of leaky Rayleigh waves is quite small, which is not conducive for defect detection and imaging. It simulates and analyzes the propagation characteristics and defect echo characteristics of the leaky Rayleigh waves, applies

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... pal component analysis (PCA) to separate the interference waves from the echo signal, then uses the Wavelet-based hidden Markov models (WHMM) algorithm to separate the systematic noise from the whole signal, combines the two methods to extract the defect information in the leaky Rayleigh waves signal, and finally uses the frequency-domain synthetic aperture focusing technology(F-SAFT) to conduct a high resolution ratio reconstruction for the data of the leaky Rayleigh waves scanning. The results show that compared with the conventional B-scan imaging, the PCA-WHMM-based ultrasonic leaky Rayleigh waves F-SAFT imaging method improves the SNR of the echo signal by 10.05 dB and reduces the average imaging error by 26.3%,which provides an effective method for the detection of metal surface and sub-surface defects. Key words:ultrasonic nondestructive testing;leaky Rayleigh waves;principal component analysis;wavelet-based hidden Markov models;frequency-domain synthetic aperture focusing * 国家自然科学基金(52075049)和湖南省自然科学杰出青年基金(2020JJ2028) 资助项目。20200825 收到初稿,20210305 收到修改稿