基于小波包变换的金属材料超声防伪识别
Ultrasonic Anti-counterfeiting Identification for Metal Material Based on Wavelet Packet Transform
摘 要
以三种成分相异和三种成分相近的金属材料为试样，提取了10 MHz的高频超声脉冲在其内部传播时的散射信号，通过小波包变换得到散射信号在尺度空间上的能量分布，并将其作为信息防伪识别特征，再采用遗传算法优化后的BP神经网络作为分类器。结果表明，提出的方法可以成功识别成分相异和成分相近的金属材料，相比于成分相近未经热处理的金属材料，同种金属经高温热处理后更容易识别，该方法亦可用于对未知金属的防伪识别。
金属材料
散射信号
BP神经网络
wavelet packet transform
metal material
scattering signal
BP neural network
Abstract
Three kinds of metal materials with different composition and three kinds of metal materials with similar composition are taken for samples in this work, and the 10 MHz ultrasonic scattering signal in the samples of the materials was extracted. The anti-counterfeiting features in the scattering signal can be got by the wavelet packet transform. The genetic algorithm was used to optimize BP neural network as classifier. Results show that the metal materials with different composition and the metal materials with similar composition can be identified successfully. Compared with the similar composition of metal materials without heat treatment, the heat treated ones are easier to be identified. Also this method can be used in the anti-counterfeiting identification of unknown metal, and it has therefore a certain practicality.
中图分类号 O426.9 TG115.28 DOI 10.11973/wsjc201707005
所属栏目 试验研究
基金项目 国家自然科学基金资助项目（11374201）
收稿日期 2016/10/11
修改稿日期
网络出版日期
作者单位点击查看
备注卢康(1991-),男,硕士研究生,主要研究方向为信号处理
引用该论文: LU Kang,HE Xiping,AN Xiaoxiao,HE Shengping,NI Tao. Ultrasonic Anti-counterfeiting Identification for Metal Material Based on Wavelet Packet Transform[J]. Nondestructive Testing, 2017, 39(7): 23～27
卢康,贺西平,安笑笑,贺升平,尼涛. 基于小波包变换的金属材料超声防伪识别[J]. 无损检测, 2017, 39(7): 23～27
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【5】LI J,YANG L,ROKHLIN S I.Effect of texture and grain shape on ultrasonic backscattering inpolycrystals[J].Ultrasonics,2014,54(7):1789-1803.
【6】刘小荣,贺西平,张宏谱,等. 金属材料的超声衰减特征及辨识的新方法[J].科学通报:2016,61(8):844-854.
【7】卢康,贺西平,崔东,等.一种基于计算相关系数的相近金属材料的超声辨识方法[J].云南大学学报(自然科学版),2015,37(3):410-414.
【8】刘小荣,贺西平,崔东,等.基于超声衰减谱的金属材料无损辨识[J].无损检测, 2015,37(11):47-50.
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【10】LOBKIS O I,ROKHLIN S I.Characterization of ploycrystals with elongated duplex microstructure by inversionof ultrasonic backscattering data[J].Applied Physics Letters,2010,96(16):1-3.
【11】贺西平,田彦平,张宏普.超声无损评价金属材料晶粒尺寸的研究[J].声学技术,2013,32(6):445-451.
【12】刘文贞,陈红岩,袁月峰,等.基于遗传算法的小波神经网络在多组分气体检测中的应用[J].传感技术学报,2016,29(7):1109-1114.
【13】施成龙,师芳芳,张碧星.利用深度神经网络和小波包变换进行缺陷类型分析[J].声学学报,2016,41(4):499-505.
【14】于亚萍,孙立宁,张峰峰,等.基于小波变换的多特征融合sEMG模式识别[J].传感技术学报,2016,29(4):512-517.
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