超声检测信号时频邻域自适应消噪技术

分析超声检测回波信号中噪声的组成和特性.考虑缺陷信号和噪声分量的分布差异,提出一种基于小波包变换时频邻域统计特征的自适应消噪方法.该方法根据噪声水平和邻域数据的方差,自动调节邻域数据对中心点值的平滑处理强度,从而达到自适应消噪目的.由于不存在参考信号和参数选择的问题,该方法稳健性好.仿真和实测信号的试验结果表明:该方法能有效提高信号的信噪比以及不同类型缺陷信号之间的可区分性,并抑制波形失真和信号的能量衰减.

TIME FREQUENCY NEIGHBORHOOD ADAPTIVE DE-NOISE METHOD OF ULTRASONIC INSPECTION SIGNALS

The composition of noises and their characters in ultrasonic echo signals are analyzed. Considering the distinct-ness of distribution between defects signals and noises, a time frequency neighborhood adaptive de-noise method based on wavelet packet transform is presented. According to the noise level and the variance in a neighborhood region, the smooth density to the center point value is adjusted adaptively, which approaches to an adaptive de-noise process. For no parameter or reference signal is needed, this method is robust. Experiments with both simulated signals and measured signals have been carried out, and the result show that this method can improve the signal noise ratio and the distinguishability between signals of different defects classes, and suppress energy attenuation as well as signal distortion efficiently.