分析试验室2025,Vol.44Issue(1) :1-8.DOI:10.13595/j.cnki.issn1000-0720.2023102301

基于固-液纳米发电机的润滑油水分检测

Detection of water content in lubricating oil based on solid-liquid nanogenerator

李招招 吴伟强 江欣 张世波 张梅 王广翔 张彬
分析试验室2025,Vol.44Issue(1) :1-8.DOI:10.13595/j.cnki.issn1000-0720.2023102301

基于固-液纳米发电机的润滑油水分检测

Detection of water content in lubricating oil based on solid-liquid nanogenerator

李招招 1吴伟强 2江欣 1张世波 1张梅 1王广翔 3张彬1
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作者信息

  • 1. 大连海事大学轮机工程学院,大连 116026
  • 2. 河北建投海上风电有限公司,唐山 063600
  • 3. 大连海事局长兴岛海事处,大连 116001
  • 折叠

摘要

本研究以润滑油为研究对象,应用固-液纳米发电机技术,设计了一种非侵入式润滑油水分双重检测单元传感器.当双检测单元的2个输出信号中的1个峰值达到对应的阈值时,便可实现润滑油水分的高效检测.通过多物理场仿真模拟和实验研究,阐述了检测单元的工作原理.通过采集非侵入式润滑油水分双重检测单元传感器的输出性能,研究了传感器检测电极长度、液体流动速度以及润滑油中水分对输出性能的影响.结果显示,润滑油中水分含量与输出性能呈正相关,该传感器可以检测0.250%~1.000%的低水分含量.最后,通过实验验证了该传感器的稳定性和可重复性,输出性能最大误差为0.19%,为润滑油水分检测提供了一种新方法.

Abstract

This study focuses on lubricating oil and employs solid-liquid nanogenerator technology to devise a non-invasive dual-detection sensor unit for monitoring water content in lubricating oil.Efficient detection of water content is achieved when either of the two output signals from the dual-detection unit reaches its corresponding threshold peak.The operational principles of the sensor unit are elaborated through comprehensive simulations involving multiple physical fields and experimental investigations.The research explores the impact of parameters such as detection electrode length,liquid flow velocity,and water content in the lubricating oil on output performance by collecting output data from the non-invasive dual-detection sensor unit.The results indicate a positive correlation between the water content in lubricating oil and the output performance,enabling the detection of low water content ranging from 0.250%to 1.000%by this sensor.Lastly,experimental validation confirms the sensor's stability and repeatability,with a maximum output performance error of merely 0.19%.This research offers a novel approach for the detection of water content in lubricating oil.

关键词

非入侵式检测/在线检测/润滑油分析/机械故障诊断/纳米发电机

Key words

non-invasive detection/online detection/lubricating oil analysis/mechanical fault diagnosis/nanogenerator

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出版年

2025
分析试验室
北京有色金属研究总院 中国分析测试协会

分析试验室

北大核心
影响因子:1.171
ISSN:1000-0720
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