中文摘要：

超声T0FD检测信号中混人的无关噪声常导致从检测图像中难以分辨缺陷特征.本研究通过小波包分解技术分析缺陷衍射波特征信号的时、频域分布特征,采用小波包统-阈值对超声T0FD 检测信号进行降噪处理,对比软、硬阈值函数对检测信号的降噪结果.研究结果表明采用软、硬阈值对长度10 mm、深度5 mm的裂纹缺陷信号降噪,其信噪比由原始的22.88 dB 分别提高至186.66、176.65 dB,对长度28 mm、深度8 mm的夹杂缺陷信号降噪,其信噪比由原始的16.62dB 分别提高至33. 74、2 8 .16 dB;基于小波包软、硬阈值去噪后信号进行图像重构可有效抑制干扰条纹并提高缺陷特征图像的分辨力,而采用软阈值法几乎完全去除了原始超声T0FD检测图像中的噪声条纹.

英文摘要：

Noise in ultrasonic T0FD testing signal often leads to difficulties in identifying the defect accurately. Wavelet packetdecomposition technique was adopted to analyze the characteristics of defect ’ s signals in time and frequency domain. Thedenoising of the ultrasonic T0FD detection signal is carried out by the wavelet packet sqtwolog, the noise reduction results of thesoft and hard threshold function were compared. The results indicate that the soft and hard threshold is applied to the length of 10mm,the depth of 5 mm crack defect signal denoising, the signal-to-noise ratio is increased from the original 22. 88 dB to 186. 66dB and 176.65 dB respectively,the soft and hard threshold is applied to length of 28 mm,the depth of 8 mm inclusion defectsignal denoising,the signal-to-noise ratio is increased from the original 16. 62 dB to 33. 74 dB and 28. 16 dB respectively. Basedon the wavelet packet soft and hard threshold denoising, the image reconstruction can effectively suppress the interference fringesand improve the resolution of the defective feature image,and the soft threshold method is used to completely remove the noisefringes in the original ultrasonic T0FD detection image.