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粗晶材料超声检测时 ,严重的结构噪声使信噪比很低。为了提高信噪比 ,增加粗晶材料超声检测的可靠性 ,人们在数字信号处理方法中做了大量工作。信号平均、滤波、卷积、频谱分析及时频分析等信号处理方法都获得过应用。小波分析是一种时频分析技术 ,具有自适应的带宽 ,适合于时变的超声缺陷信号的处理 ;用于粗晶材料的信号处理时 ,比其它方法获得的信息要丰富得多 ,且能大幅度提高信噪比
When the coarse-grained material is ultrasonically tested, the serious structural noise makes the signal-to-noise ratio very low. In order to improve the signal-noise ratio and increase the reliability of the ultrasonic testing of coarse-grained materials, a great deal of work has been done in the digital signal processing method. Signal averaging, filtering, convolution, spectrum analysis and time-frequency analysis and other signal processing methods have been applied. Wavelet analysis is a time-frequency analysis technique with adaptive bandwidth suitable for the processing of time-varying ultrasonic flaw signals; for signal processing of coarse-grained materials, the information obtained is much richer than other methods and can Significantly improve the signal to noise ratio