金属材料小缺陷超声反射信号建模及识别

为了能从含噪声金属材料超声检测信号中有效识别出微小缺陷回波,建立了金属材料超声反射信号模型并提出了基于相关系数的微小缺陷回波识别方法。对含微小缺陷金属材料超声脉冲反射信号的成分进行分析,建立了基于散射声场与高斯回波理论的优化超声回波模型。设计了超声缺陷回波位置识别方法。该方法对超声脉冲反射信号去噪后,取探头发射脉冲信号为参考信号;然后与去噪后的信号逐段求解相关系数;最后对该相关系数序列进行阈值化处理,获得缺陷回波在超声回波信号中的位置。将利用上述优化超声回波模型生成的超声反射信号及其频谱与实验获得的金属材料超声反射信号及其频谱进行了对比,结果表明:两者的时频域特征具有一致性。当将阈值设定为相关系数序列最大值的60%时,能够有效从超声背散射信号中识别出金属材料微小缺陷回波。

Ultrasonic echo signal modeling and identification for minor defects in metallic materials

To identify the minor defect echo from ultrasonic testing signals containing the noise of metallic materials, an ultrasonic echo signal model was established and a minor defect echo identification method was put forward. The composition of ultrasonic pulse echo signals with minor defects obtained from metallic materials was analyzed, and then optimized ultrasonic echo model was established based on the Gaussian echo theory and a scattering sound field. The identification method for echo locations of ultrasonic minor defects was designed. By proposed method, the ultrasonic pulse echo signal was first denoised. Then the pulse signal from a probe was taken as the reference signal and the correlation coefficient between reference signal and denoised signal was piecewise calculated. Finally, the correlation coefficient sequence was processed by threshold method and the location of flaw echo in the ultrasonic echo signal was obtained. The simulation signal and frequency spectra generated by the optimized ultrasonic echo model were compared with those of experimental ultrasonic signal. The experiment results show that the time and frequency domain features of the two signals are in good agreements. When the threshold is set as 60 percent of the max value of the correlation coefficient sequence, the minor flaw echo can be accurately identified from the ultrasonic echo signals of metallic materials.