基于电涡流的金属种类识别技术的理论与实验研究  

Theoretical and experimental study on metal type identification based on eddy current

作　　者：曹青松[1] 周继惠[1] 

机构地区：[1]华东交通大学机电工程学院,南昌330013

出　　处：《仪器仪表学报》2007年第9期1718-1722,共5页Chinese Journal of Scientific Instrument

摘　　要：通电线圈与其附近的金属导体之间将产生电涡流效应,由于不同种金属有着不同的电导率和磁导率,从而使得相应的探测线圈等效阻抗的变化量互不相同。本文用电容三点式振荡电路将线圈等效阻抗的变化转换成电压信号,通过离线训练的方法获得神经网络辨识模型,以此来进行金属种类的识别。本文设计了一套基于微机检测系统为核心的电涡流金属种类识别的实验装置,选用实验室易获得的吸铁、黄铜和铝合金3种金属为对象展开实验研究,结果表明利用电涡流技术以及神经网络辨识的方法能有效的识别金属种类,为智能金属探测器的推广应用奠定了理论基础。Eddy current is presented in electric coil when it approaches metallic conductor. Different metals have different conductivity and permeability, therefore the equivalent impedances of the electric coil are also different. The coil equivalent impedance is transformed into voltage signal using three-point capacitance oscillator. The neural network model is obtained through off-line training, which is used to identify the type of the metals effectively. A complete set of eddy current test system was designed based on microcomputer. Three types of metals-magnetic iron, brass and aluminum alloy that are easy to find were used to carry out experimental study. Experimental results show that the eddy current technology and neural network can be used to identify metal types effectively. The study provides a basis for the broad application of intelligent metal detectors.

关 键 词：涡流检测 金属种类识别 神经网络 微机检测系统 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]