作者：张勇, 王丹丹, 蒙国尤, 于善虎

作者单位：华南理工大学机械与汽车工程学院，广东 广州 510640

关键词：润滑油;金属磨粒;传感器;电磁感应

摘要：

通过对润滑油中金属磨粒的尺寸、数量和材质等进行检测识别，能够判断发动机的磨损部位及磨损程度，进而对发动机进行针对性的保养维护，对提高发动机工作的可靠性具有重要意义。以新型电感式润滑油金属磨粒检测传感器为研究对象，对传感器磁场分布、铁铜磨粒对磁场的扰动特性进行仿真分析。提出一种以多层矩形线圈为核心的传感器结构，阐述电感式金属磨粒检测传感器的检测原理。通过Ansys Maxwell软件对影响线圈电感与金属磨粒函数关系的因素进行仿真分析，验证设计的传感器结构的可行性。最后，试验验证传感器检测金属磨粒的性能。结果表明：该传感器能够在截面积为10 mm²的流道中识别不小于50 μm的铁磨粒及不小于100 μm的铜磨粒。

Research on metal abrasive particle detection technology of lubricating oil based on electromagnetic induction
ZHANG Yong, WANG Dandan, MENG Guoyou, YU Shanhu
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China
Abstract: Through the detection and identification of the size, quantity and material of the metal abrasive particles in the lubricating oil, the wear position and degree of the engine can be judged, and then the targeted maintenance of the engine is of great significance to improve the reliability of the engine. The magnetic field distribution and the disturbance characteristics of iron and copper abrasive particles to the magnetic field of the new inductive lubricating oil abrasive detection sensor are simulated and analyzed. This paper presents a sensor structure with multi-layer rectangular coil as the core, and describes the detection principle of inductive metal abrasive particle detection sensor. Ansys Maxwell software was used to simulate and analyze the factors affecting the relationship between the inductance of the coil and the function of the abrasive particles of the metal, and the feasibility of the designed sensor structure was verified. Finally, the performance of the sensor to detect metal abrasive particles is tested and studied. The results show that the sensor can identify iron grinding particles no less than 50 μm and copper grinding particles no less than 100 μm in a 10 mm² flow passage.
Keywords: lubricating oil;metal abrasive particles;sensor;electromagnetic induction
2020, 46(12):15-21  收稿日期: 2020-09-21;收到修改稿日期: 2020-10-28
基金项目:
作者简介: 张勇(1969-),男,河北保定市人,教授,博士,主要从事车辆电子、摩擦学、润滑油等方面的研究
参考文献
[1] 李勇. 某型航空发动机润滑系统故障诊断的研究[D]. 武汉: 武汉理工大学, 2010.
[2] 孟庆民. 润滑油液污染颗粒监测系统与实验研究[J]. 传感器与微系统, 2007, 26(3): 31-33
[3] 于永妍. 浅析油液监测技术在船舶机械维修决策中的应用[J]. 中国高新技术业, 2016(1): 47-48
[4] 张宇翔, 宣征南, 孙志伟, 等. 基于油液监测技术的齿轮箱运行状态模糊综合评价[J]. 现代制造工程, 2017(11): 22-28
[5] MILLER J L, KITALJEVICH D. In-line oil debris monitor for aircraft engine condition assessment[C]//Aerospace Conference Proceedings, 2000 IEEE. IEEE, 2000.
[6] BARRACLOUGH T, HENNING P, SCIENTIFIC A S, et al. Detection of abnormal wear particles in hydraulic fluids via electromagnetic sensor and particle imaging technologies[J]. Spectro Scientific, Chelmsford, MA, 2018
[7] 龚人杰, 武通海, 张小刚. 基于电感量测量的润滑油在线磨粒传感器设计[C]//第十一届全国摩擦学大会论文集, 2013: 68-72.
[8] 薄昭. 基于微流体的油液金属磨粒区分检测实验研究[D]. 大连: 大连海事大学, 2015.
[9] 殷勇辉, 严新平, 萧汉梁. 电感式磨粒监测传感器的磁场均匀性研究[J]. 摩擦学学报, 2001, 21(3): 228-231
[10] DU L, ZHE J, CARLETTA J, et al. Real-time monitoring of wear debris in lubrication oil using a microfluidic inductive Coulter countingdevice[J]. Microfluidics and nanofluidics, 2010, 9(6): 1241-1245
[11] LI B, YANG D, HU Z, et al. Theoretic modeling and numerical simulation of the electromagnetic sensor for online wear debris monitoring[C]//International Conference on Quality, Reliability, Risk, Maintenance, & Safety Engineering, 2013.
[12] WU Y, ZHANG H. An approach to calculating metal particle detection in lubrication oil based on a micro inductive sensor[J]. Measurement Science & Technology, 2017, 28(12): 125101