Efficient and accurate nondestructive testing of surface or sub-surface flaws is essential for metal components. This study focuses on the high-quality image reconstruction of these flaws. An imaging detection method is introduced which combines the leaky Rayleigh waves testing and the synthetic aperture focusing technique (SAFT) with an immersion pulse-echo scanning. The principal component analysis (PCA) is used to reduce the noise of the leaky Rayleigh waves, and then the imaging is obtained using the SAFT algorithm. The experimental results show that the PCA-SAFT imaging method can reduce structural noise and imaging artifacts comparing with the B-scan imaging method. The lateral resolution of defects is improved and the mean error of defects sizing can be reduced by 48.81%. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the ultrasonic image are increased by 6.95 dB and 4.20 dB respectively. The proposed method can be a new choice for effective evaluating the surface quality of key components.

对于金属部件，有效而准确的表面或亚表面缺陷的无损检测至关重要。这项研究的重点是这些缺陷的高质量图像重建。介绍了一种成像检测方法，该方法将泄漏的瑞利波测试和合成孔径聚焦技术（SAFT）与沉浸式脉冲回波扫描技术相结合。主成分分析（PCA）用于减少泄漏的瑞利波的噪声，然后使用SAFT算法获得成像。实验结果表明，与B扫描成像方法相比，PCA-SAFT成像方法可以减少结构噪声和成像伪影。改善了缺陷的横向分辨率，可以将缺陷尺寸的平均误差降低48.81％。超声图像的信噪比（SNR）和对比度噪声比（CNR）分别增加了6.95 dB和4.20 dB。所提出的方法可能是有效评估关键部件表面质量的新选择。