基于超声检测的无人机复合材料多特征提取研究  

UItrasonic Testing Based MuIti-feature Extraction of UAV Composite MateriaIs

作　　者：王峰林[1] 王长龙[1] 胡永江[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：《计量学报》2014年第6期612-616,共5页Acta Metrologica Sinica

基　　金：武器装备预先研究项目

摘　　要：在超声检测无人机复合材料脱粘缺陷时，针对单一特征提取方法信息利用不充分、不同特征对识别重要程度不同的问题，分析超声回波信号特性，提出一种将小波包域和时域相结合的多特征提取方法。该方法首先对信号进行小波包分解，获得小波包域特征，并利用主成分分析法对该特征进行降维处理；然后结合复合材料特性提取信号的时域特征；最后将提取的不同域特征组合，并对组合特征向量进行加权处理。对处理后的特征向量运用类别可分性测度准则进行评价，结果表明提取的信号特征能较好地界定复合材料的脱粘等缺陷。Due to the single feature extraction has not exert information as well as different features have different importance while recognizing UAV composite materials flaws, a method for multi-feature extraction in wavelet packet field and time - field is proposed. The new approach firstly decomposes signal with wavelet packet to get feature, using principal component analysis to decrease the dimension of feature vectors, then, extracts time - field feature considering composite materials characters, at last, the combined feature vectors algorithm is proposed using the matching method. The experimental results indicate the effectiveness of the proposed feature vectors while classifying the bond flaws in composite materials.

关 键 词：计量学 超声检测 特征提取 主成分分析 加权匹配 无人机 复合材料 

分 类 号：TB95[一般工业技术—计量学]