基于电感式传感器的金属颗粒材质识别及粒径估计

Metal particle material identification and size estimation based on the inductive sensor

传统的电感式颗粒传感器输出的是电感或电压幅值的脉冲信号,本质为标量信号。可通过脉冲信号的正负性区分金属颗粒是磁性或非磁性,且只能在已知颗粒材质的情况下估计颗粒的粒径。但在含有多种金属颗粒的油液中,基于标量信号的颗粒识别方法将失效。为此,本文采用了一种双锁相放大电路,将颗粒产生的复数域信号转化为一对直流信号。提出一种基于模糊隶属度函数的信号处理方法,实现了在噪音干扰下多种颗粒的材质识别和粒径估计。本文搭建了三线圈传感器实验系统。利用五种金属颗粒构建了隶属度函数,并进行系统标定。最后选取两种颗粒对标定后的系统进行了验证。结果表明系统对颗粒材质的识别准确,粒径估计误差小于2%。

The output of the traditional inductive particle sensor is pulse signal of inductance or voltage amplitude,which is scalar signal in nature.The metal particle can be distinguished into magnetic metal or non-magnetic particle by the positive and negative of pulse signal.The particle size can only be estimated under the condition of known particle material.However,for oil containing multiple metal particles,the particle identification method based on the scalar signal may be invalid.To solve this problem,a double lock-in amplifier circuit is utilized to convert the complex particle signal into a pair of DC signals.A signal processing method based on fuzzy membership function is proposed,which can realize the material identification and size estimation of various particles under noise interference.In this paper,an experimental system based on a three-coil sensor is established.The fuzzy membership function is formulated and the system is calibrated by using five kinds of metal particles.Finally,two kinds of particles are selected to evaluate the calibrated system.Results show that the particle material can be identified accurately by this system,and the error of particle size estimation is less than 2%.