摘要
声-超声检测信号中存在的大量系统和环境噪声,严重影响回波信号的读取。采用平均滤波和小波包变换的方法进行消噪。利用二阶Daubechies小波函数建立一小波包消噪模型,对信号进行分解重构。经过处理后,消噪效果比较明显,能更加完整地保留有用信息。
There are large amount of systemic and environmental noises in acoustic-ultrasonic monitoring signals,which seriously affect the readings of actual echo signals.In this paper,the methods of even filtering and wavelet packet transform are employed to reduce the noise.Then,a wavelet noise reduction model is established by using the second-order Daubechies wavelets function.The signals are decomposed and reconstructed.The results show that after the processing the noise can be removed obviously and the useful signals can be reserved completely.
出处
《噪声与振动控制》
CSCD
北大核心
2010年第6期145-148,共4页
Noise and Vibration Control
关键词
声学
声-超声
平均滤波
小波包
消噪
acoustic
ultrasonic
even filtering
wavelet packet
noise reduction
