摘要
为了解决超声波检测粗晶材料时回波信噪比低、缺陷难以检出的难题,对超声波信号小波分析原理进行了研究。以实例分析的方式提出小波尺度加权降噪法,并阐述其原理及优点。在小波分析尺度加权降噪法的基础上编制了缺陷识别程序,对超声波信号进行处理,大大提高了对缺陷的识别与定位能力。该检测工艺在实际粗晶材料超声检测中取得了良好的效果。
A difficult problem of ultrasonic testing of coarse-grained material was the low signal to noise ratio(SNR). In order to solve the problem, wavelet analysis principle for ultrasonic signal was hence researched. Wavelet scale pruning de-noising method was put forward and its advantages were introduced. On the basis of it, the program for defect recognition was programmed and used in ultrasonic signal processing, so the ability for recognition and location of defect was improved highly. Test in practice proved that the method was effective for coarse-grained materials.
出处
《无损检测》
北大核心
2005年第4期179-182,共4页
Nondestructive Testing
关键词
超声波检测
粗晶材料
信噪比
小波尺度加权法
Ultrasonic testing
Coarse-grained material
Signal to noise ratio
Wavelet scale pruning de-noising method
