(西安交通大學(xué)機(jī)械工程學(xué)院， 西安 710049)
摘 要: 在超聲無損檢測(cè)中，粗晶材料（奧氏體鋼）的晶粒噪聲往往使材料的缺陷信號(hào)變得難以識(shí)別。在分析晶粒噪聲和缺陷信號(hào)頻譜分布的基礎(chǔ)上，利用小波分析法消 除晶粒噪聲以實(shí)現(xiàn)有效識(shí)別缺陷的目標(biāo)。利用此方法進(jìn)行實(shí)際粗晶材料超聲信號(hào)分析可方便地識(shí)別缺陷的存在與否以及缺陷的位置。
關(guān)鍵字: 粗晶 超聲波 無損檢測(cè) 小波變換
（School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049）
Abstract:
It was difficult to identify the ultrasonic defect signals of coarse grained materials, so a wavelet analysis method was applied to reduce the grained noise based on the discussion of the frequency spectrum distribution of the defect signals and grained noise. The experimental results show that the SNR can be improved highly by this method.
Key words: coarse-grain ultrasound nondestructive testing wavelet transform
