基于EMD的改进小波阈值降噪法在超声信号处理中的应用  

Application of Improved Wavelet Threshold De-noising Based on Empirical Mode Decomposition on Ultrasonic Signal Processing

作　　者：王峰林[1] 王长龙[1] 朱红运[1] 

机构地区：[1]军械工程学院无人机工程系,河北石家庄050003

出　　处：《军械工程学院学报》2013年第3期35-39,共5页Journal of Ordnance Engineering College

基　　金：军队科研计划项目

摘　　要：针对超声检测回波信号中的大量噪声，分析了超声检测回波信号的特性，考虑经验模式分解（EMD）和小波哗噪的优点，在改进阈值函数基础上提出一种基于EMD的小波阈值降噪方法．该方法利用EMD对超声信号进行分解，对高频分量用改进小波阈值函数方法进行处理，再结合低频分量重构得到降噪信号．仿真实验结果表明，该方法降噪效果优于小波软、硬阂值降噪，进一步提高了重建信号的信噪比，降低了其均方根误差，是一种可行的超声信号降噪方法．With regard to the noise contained in the ultrasonic testing echo signal, the characteristics of ultrasonic testing echo signal are analyzed. Considering the advantages of EMD and wavelet de-noising, an improved wavelet threshold de-noising method is proposed based on empirical mode decomposition（EMD）. The new approach decomposes signal by EMD, then combines the high frequencies dealt with the improved wavelet threshold function with the low frequencies to attain the de-noising signal. The simulation and experimental results indicate that the new method has better effect than the hard and soft threshold on the signal de-noising which can obtain higher signal-to- noise ratio and lower mean squared error. The new approach is a feasible de-nosing algorithm for ultrasonic signal.

关 键 词：超声检测 经验模式分解 降噪 小波变换 

分 类 号：TB553[理学—物理]