焊缝超声TOFD检测信号及图像降噪技术研究

超声TOFD检测信号中混入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，采用小波包统一阈值对超声TOFD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16.62 dB分别提高至33.74、28.16 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TOFD检测图像中的噪声条纹。

Research on Noise Reduction Technology of Ultrasonic TOFD Signal and Image of Weld

Noise in ultrasonic TOFD testing signal often leads to difficulties in identifying the defect accurately.Wavelet packet decomposition technique was adopted to analyze the characteristics of defect's signals in time and frequency domain.The denoising of the ultrasonic TOFD detection signal is carried out by the wavelet packet sqtwolog, the noise reduction results of the soft and hard threshold function were compared.The results indicate that the soft and hard threshold is applied to the length of 10 mm, the depth of 5 mm crack defect signal denoising, the signal-to-noise ratio is increased from the original 22.88 dB to 186.66 dB and 176.65 dB respectively, the soft and hard threshold is applied to length of 28 mm, the depth of 8 mm inclusion defect signal denoising, the signal-to-noise ratio is increased from the original 16.62 dB to 33.74 dB and 28.16 dB respectively.Based on the wavelet packet soft and hard threshold denoising, the image reconstruction can effectively suppress the interference fringes and improve the resolution of the defective feature image, and the soft threshold method is used to completely remove the noise fringes in the original ultrasonic TOFD detection image.