Pardo E, San Emeterio J L, Rodriguez M A, Ramos A
Dpto. Señales, Sistemas & Tecnologías Ultrasónicas, Instituto de Acústica (CSIC), Serrano 144, 28006 Madrid, Spain.
Ultrasonics. 2006 Dec 22;44 Suppl 1:e1063-7. doi: 10.1016/j.ultras.2006.05.101. Epub 2006 Jun 6.
Translation-invariant wavelet processing is applied to grain noise reduction in ultrasonic non-destructive testing of materials. In particular, the undecimated wavelet transform (UWT), which is essentially a discrete wavelet transform (DWT) that avoids decimation, is used. Two different UWT processors have been specifically developed for that purpose, based on two UWT implementation schemes: the "à trous" algorithm and the cycle-spinning scheme. The performance of these two UWT processors is compared with that of a classical DWT processor, by using synthetic grain noise registers and experimental pulse-echo NDT traces. The synthetic ultrasonic traces have been generated by an own-developed frequency-domain model that includes frequency dependence in both material attenuation and scattering. The experimental ultrasonic traces have been obtained by inspecting a piece of carbon-fiber reinforced plastic composite in which we have mechanized artificial flaws. Decomposition level-dependent thresholds, which are suitable for correlated noise, are specifically determined in all cases. Soft thresholding, Daubechies db6 mother wavelet and the three well-known threshold selection rules, Universal, Minimax and SURE, are applied to the different decomposition levels. The performance of the different de-noising procedures for single echo detection has been comparatively evaluated in terms of signal-to-noise ratio enhancement.
平移不变小波处理应用于材料超声无损检测中的颗粒噪声降低。具体而言,使用了非下采样小波变换(UWT),它本质上是一种避免下采样的离散小波变换(DWT)。基于两种UWT实现方案,即“à trous”算法和循环旋转方案,专门为此开发了两种不同的UWT处理器。通过使用合成颗粒噪声记录和实验脉冲回波无损检测迹线,将这两种UWT处理器的性能与传统DWT处理器的性能进行了比较。合成超声迹线由自行开发的频域模型生成,该模型包括材料衰减和散射中的频率依赖性。实验超声迹线是通过检测一块含有机械加工人工缺陷的碳纤维增强塑料复合材料获得的。在所有情况下,都专门确定了适用于相关噪声的与分解级别相关的阈值。软阈值处理、Daubechies db6母小波以及三种著名的阈值选择规则,即通用规则、极小极大规则和Sure规则,应用于不同的分解级别。已根据信噪比增强对不同单回波检测去噪程序的性能进行了比较评估。