An Inductive Debris Sensor Based on a High-Gradient Magnetic Field

被引:64
作者
Feng, Song [1 ]
Yang, Leilei [1 ]
Qiu, Guang [1 ]
Luo, Jiufei [1 ]
Li, Rui [1 ]
Mao, Junhong [2 ]
机构
[1] Chongqing Univ Posts & Telecommun, Sch Adv Mfg Engn, Chongqing 400065, Peoples R China
[2] Xi An Jiao Tong Univ, Dept Mech Engn, Xian 410073, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Inductive debris sensor; high-gradient magnetic field; on-line wear monitoring; WEAR DEBRIS;
D O I
10.1109/JSEN.2018.2890687
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The health condition of mechanical systems can be characterized by wear debris in lube oil. Therefore, wear debris detection is necessary for the fault prediction and diagnosis of mechanical systems. This paper presents an inductive debris sensor based on a high-gradient magnetic field. An induction coil is placed in a high-gradient magnetic field, and an induced voltage is generated when wear debris in the oil pipe flows through a magnetic field. A mathematical model of the sensor is established, and the output signal of the sensor is similar to that of a three-coil inductive debris sensor. The experimental results show that the sensor is capable of detecting 2.5-mu m ferromagnetic particles. The sensor driven by a constant current has a simple structure and is feasible for on-line wear monitoring.
引用
收藏
页码:2879 / 2886
页数:8
相关论文
共 18 条
[1]   Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method [J].
Du, Li ;
Zhu, Xiaoliang ;
Han, Yu ;
Zhao, Liang ;
Zhe, Jiang .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2013, 24 (07)
[2]   Parallel sensing of metallic wear debris in lubricants using undersampling data processing [J].
Du, Li ;
Zhe, Jiang .
TRIBOLOGY INTERNATIONAL, 2012, 53 :28-34
[3]   A high throughput inductive pulse sensor for online oil debris monitoring [J].
Du, Li ;
Zhe, Jiang .
TRIBOLOGY INTERNATIONAL, 2011, 44 (02) :175-179
[4]   AN INDUCTIVE METHOD FOR ESTIMATING THE COMPOSITION AND SIZE OF METAL PARTICLES [J].
FLANAGAN, IM ;
JORDAN, JR ;
WHITTINGTON, HW .
MEASUREMENT SCIENCE AND TECHNOLOGY, 1990, 1 (05) :381-384
[5]   Electrostatic wear monitoring of rolling element bearings [J].
Harvey, T. J. ;
Wood, R. J. K. ;
Powrie, H. E. G. .
WEAR, 2007, 263 :1492-1501
[6]   A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity [J].
Hong, Wei ;
Wang, Shaoping ;
Liu, Haokuo ;
Tomovic, Mileta M. ;
Chao, Zhang .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 82 :1-12
[7]   A new debris sensor based on dual excitation sources for online debris monitoring [J].
Hong, Wei ;
Wang, Shaoping ;
Tomovic, Mileta M. ;
Liu, Haokuo ;
Wang, Xingjian .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2015, 26 (09)
[8]   A direct reflection OLVF debris detector based on dark-field imaging [J].
Li, Bo ;
Xi, Yinhu ;
Feng, Song ;
Mao, Junhong ;
Xie, You-Bai .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2018, 29 (06)
[9]   Mathematical Model, Simulation, and Experimental Calibration of Electrostatic Wear-Site Sensor [J].
Liu Ruochen ;
Zuo Hongfu .
IEEE SENSORS JOURNAL, 2017, 17 (08) :2428-2438
[10]   The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery [J].
Loutas, T. H. ;
Roulias, D. ;
Pauly, E. ;
Kostopoulos, V. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2011, 25 (04) :1339-1352