噪音(视频)
信号(编程语言)
粒子(生态学)
放大器
领域(数学分析)
材料科学
物理
电子工程
拓扑(电路)
电气工程
计算机科学
工程类
数学
数学分析
人工智能
CMOS芯片
地质学
图像(数学)
程序设计语言
海洋学
作者
Yehui Li,Changli Yu,Bo Xue,Hongpeng Zhang,Xingming Zhang
标识
DOI:10.1109/tim.2021.3130926
摘要
The detection of metal particles in oil is of great significance to the fault diagnosis of mechanical equipment. Real domain detection methods cannot simultaneously identify the sizes and materials of particles. Because a metal particle in an alternating magnetic field induces a complex domain signal whose strength relates to the particle properties, this article introduces a double lock-in amplifier circuit (DLAC) into a triple-coil inductive particle sensor to detect the complex domain signal under noise interference conditions. Furthermore, various sizes of red copper, brass, aluminum, iron, and type 403 steel particles are chosen as the experimental materials. For the first time, the complex domain signals induced by the five kinds of particles are detected. Hence, in the complex plane, a method is proposed to identify the size and material of a particle based on the amplitude and phase of these signals. With the high sensitivity and strong antinoise ability of the DLAC, this system can detect 25- $\mu \text{m}$ iron particles and 70- $\mu \text{m}$ copper particles. This study presents a new strategy for the online detection of particles in oil.
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