论文部分内容阅读
采用计算机化超声信号分析系统，对奥氏体不锈钢粗晶材料缺陷的超声回波信号进行采集和加工．结果表明，小波包技术在粗晶材料缺陷超声信号时频特性的表征中具有明显优越性，并能克服裂谱处理技术的缺点．同时发现噪声主要分布在较高或较低频率的位置，而缺陷信号在中间频率段有较大的幅值分布．利用这一特征，可以根据超声信号小波包分解的结果检测到微弱的粗晶材料缺陷信号．
The computerized ultrasonic signal analysis system is adopted to collect and process the ultrasonic echo signal of austenitic stainless steel coarse grain material defects. The results show that the wavelet packet technique has obvious advantages in the characterization of the time-frequency characteristics of the coarse-grained material defect ultrasonic signals and can overcome the shortcomings of the cracked spectrum processing techniques. At the same time, it is found that the noise is mainly distributed in the higher or lower frequency position, while the defect signal has larger amplitude distribution in the intermediate frequency. Using this feature, we can detect the weak coarse-grained material defect signal based on the result of wavelet packet decomposition of ultrasonic signals.