基于自适应第二代小波的超声回波信号特征识别  

A New Method for Identifying Ultrasonic Echo Signal Features Using Adaptive Second Generation Wavelet

作　　者：姜洪开[1] 窦丹丹[1] 何正嘉[2] 

机构地区：[1]西北工业大学航空学院,陕西西安710072 [2]西安交通大学机械工程学院,陕西西安710049

出　　处：《西北工业大学学报》2011年第1期93-96,共4页Journal of Northwestern Polytechnical University

基　　金：国家自然科学基金(50975231;51075331)资助

摘　　要：文章针对强噪声背景下液压系统压力超声检测回波信号特征识别问题,构造了一种识别该类信号时域特征的自适应第二代小波方法。该方法以第二代小波为基础,以超声回波信号的峭度大小为目标函数,选择每层自适应匹配超声回波信号特征的第二代小波预测器和更新器,利用选择的预测器和更新器对信号进行预测和更新运算;根据每层自适应第二代小波分解的超声回波信号噪声水平,选取自适应匹配超声回波信号噪声特点的降噪阈值,对信号进行降噪和恢复,提取信号时域特征。该方法成功地准确识别出超声回波信号回波至点的时刻和时间间隔特征信息。结果表明,第二代小波自适应阈值方法对强噪声背景下超声回波信号特征的识别效果优于经典小波方法。To identify the features of a hydraulic system ＇ s ultrasonic echo new method for constructing adaptive second generation wavelet. This new 3. Their core consists of： （1） based on the second generation wavelet,we signal corrupted by noise, we develop a method is explained in sections 1,2 and use the size of kurtosis of ultrasonic echo signal as objective function to select its prediction operator and updating operator, each of which can adapti match its features at each level; thus, the ultrasonic el of noise of the ultrasonic echo signal decomposed we select the de-noising threshold value to de-noise echo signal is predicted and updated; （2） according to the vely lev- by using the adaptive second generation wavelet at each level, and recover the ultrasonic echo signal and extract its features in time domain. Section 4 and 5 apply our method to the feature extraction of ultrasonic echo signal; the results, given in Figs. 1 through 7, and their analysis show preliminarily that our method for constructing the adaptive second gen- eration wavelet can effectively extract the features of ultrasonic echo signal by identifying its arrival time point and the interval between two time points, indicating that our method outperforms the traditional wavelet transform methods.

关 键 词：适应第二代小波 超声回波信号 特征识别 

分 类 号：TH17[机械工程—机械制造及自动化]