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对粗晶材料的超声无损检测，超声波A扫描得到的信号中，缺陷回波之间的相关性强于晶粒噪声的相关性，因此，可以通过自适应滤波技术达到提高缺陷回波信噪比的目的．本文利用了在自适应噪声抵消中广泛应用的最小均方误差（LMS）算法。实验证明，这种方法的效果对于参数调节不敏感。
For the non-destructive ultrasonic testing of coarse-grained materials, the correlation between the defect echoes and the signal of the ultrasonic A-scan is stronger than that of the grain noises. Therefore, the adaptive filtering can be used to improve the signal-to-noise ratio the goal of. This paper takes advantage of the least mean square error (LMS) algorithm widely used in adaptive noise cancellation. Experiments show that the effect of this method is not sensitive to parameter adjustment.