跟踪(教育)
粒子(生态学)
磁层粒子运动
状态监测
粘度
领域(数学)
机械工程
机油分析
有限元法
微流控
机械
模拟
材料科学
计算机科学
工程类
物理
结构工程
纳米技术
磁场
复合材料
数学
电气工程
地质学
量子力学
海洋学
纯数学
教育学
心理学
作者
Zhenzhen Liu,Hongfu Zuo,Yan Liu,Xin Li,Zhixiong Chen
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:72: 1-11
被引量:4
标识
DOI:10.1109/tim.2023.3282677
摘要
A high-precision wear particle monitoring instrument based on numerical simulation, machine vision, multi-target tracking algorithm, and microfluidic technology is designed and developed in this paper. The instrument not only performs the traditional particle number and size detection, but also proposes a particle density detection model based on motion velocity. Firstly, an on-line visual microfluidic chip for oil particles motion was specially designed. Then a mathematical model relationship between particles velocity and particles diameter, particles density, oil viscosity, oil density was established by force analysis and solving the equation, which was used to explain the working principle of the instrument. Meanwhile, a multi-target tracking algorithm incorporating the characteristics of wear particles based on YOLOv5-Deepsort was custom-developed to detect the number, size, and motion characteristics of particles under the optical field of view of the image sensor. Secondly, the oil flow field distribution and the four factors affecting the particle motion characteristics in the self-developed chamber, particle size, particle material, particle radial position, and oil velocity were analyzed by using the finite element analysis in COMSOL. Finally, a pin-disk wear experimental validation results demonstrated this approach has excellent suitability to monitor the number, size, and density of wear particles with diameters above 20μm and densities above 2000 kg/m3 simultaneously. This portable oil particle monitoring instrument provides technical support for condition monitoring, fault diagnosis, and intelligent maintenance of rotating mechanical equipment.
科研通智能强力驱动
Strongly Powered by AbleSci AI