(西安交通大学机械工程学院, 西安 710049)
摘 要: 在超声无损检测中,粗晶材料(奥氏体钢)的晶粒噪声往往使材料的缺陷信号变得难以识别。在分析晶粒噪声和缺陷信号频谱分布的基础上,利用小波分析法消 除晶粒噪声以实现有效识别缺陷的目标。利用此方法进行实际粗晶材料超声信号分析可方便地识别缺陷的存在与否以及缺陷的位置。
关键字: 粗晶 超声波 无损检测 小波变换
(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