摘要
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 。
In the ultrasonic testing of coarse grain materials,signal to noise ratio (SNR) is very low due to the serious structure noise To enhance the SNR and reliability of ultrasonic testing of coarse grain materials,many works have been done in the application of digital signal processing methods,including signal averaging,filtering,convolution,spectrum analysis and time frequency analysis,to the testing practive in the past year Being a time frequency analysis process,wavelet analysis has a auto adaptive band,and is suitable to deal with the ultrasonic defect signal that has time variable property The utilization of wavelet analysis in signal processing of coarse grain materials leading to much more abundant information than normal program,and SNR is strengthened concretely
出处
《核动力工程》
EI
CAS
CSCD
北大核心
2000年第2期183-187,共5页
Nuclear Power Engineering
基金
北京市自然科学基金
关键词
粗晶材料
超声波检测
信号处理
奥氏体不锈钢
Coarse grain materials Austenite Ultrasonic testing Wavelet analysis Signal processing
