A New Inductive Debris Sensor Based on Dual-Excitation Coils and Dual-Sensing Coils for Online Debris Monitoring

Lubricants are of key importance for mechanical processing, and exist in nearly every mechanical system. When the equipment is in operation, debris particles will be generated in mechanical lubricants. The detection of debris particles can indicate the wear degree of machinery components, and provide prognosis warning for the system before the fault occurs. In this work, a novel type of inductive debris sensor consisting of two excitation coils and two sensing coils is proposed for online debris monitoring. The developed sensor was proven to be of high sensitivity through experimental verification. The testing results show that, using the designed sensor, ferrous metal debris with a size of 115 μm and nonferrous metal debris with a size of 313 μm in a pipe with an inner diameter of 12.7 mm can be effectively detected. Moreover, the proposed inductive debris sensor structure has better sensitivity at higher throughput and its design provides a useful insight into the development of high-quality sensors with superior performances.

[1]  Xinlin Qing,et al.  Characteristics Study of In-Situ Capacitive Sensor for Monitoring Lubrication Oil Debris , 2017, Sensors.

[2]  Hongkun Wu,et al.  Imaged wear debris separation for on-line monitoring using gray level and integrated morphological features , 2014 .

[3]  Xinyu Wang,et al.  An Inductive Debris Sensor for a Large-Diameter Lubricating Oil Circuit Based on a High-Gradient Magnetic Field , 2019 .

[4]  Jiang Zhe,et al.  Lubricating oil conditioning sensors for online machine health monitoring – A review , 2017 .

[5]  Li Du,et al.  A high throughput inductive pulse sensor for online oil debris monitoring , 2011 .

[6]  B. Drinkwater,et al.  Monitoring of Lubricant Film Failure in a Ball Bearing Using Ultrasound , 2006 .

[7]  Shaoping Wang,et al.  A new debris sensor based on dual excitation sources for online debris monitoring , 2015 .

[8]  Jiang Zhe,et al.  Parallel Sensing of Metallic Wear Debris in Lubricants Using Undersampling Data Processing , 2012 .

[9]  Joan Carletta,et al.  A microfluidic Coulter counting device for metal wear detection in lubrication oil. , 2009, The Review of scientific instruments.

[10]  Hongpeng Zhang,et al.  An approach to calculating metal particle detection in lubrication oil based on a micro inductive sensor , 2017 .

[11]  F. Choy,et al.  Real-time monitoring of wear debris in lubrication oil using a microfluidic inductive Coulter counting device , 2010 .

[12]  Ben Dong Liu,et al.  The Simulation Research of Detecting Metal Debris with Different Shape Parameters of Micro Inductance Sensor , 2013 .

[13]  Q. Wang,et al.  Monitoring of Non-Ferrous Wear Debris in Hydraulic Oil by Detecting the Equivalent Resistance of Inductive Sensors , 2018, Micromachines.

[14]  J. R. Jordan,et al.  An inductive method for estimating the composition and size of metal particles , 1990 .

[15]  Joan Carletta,et al.  Inductive Coulter counting: detection and differentiation of metal wear particles in lubricant , 2010 .

[16]  Jiang Zhe,et al.  Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method , 2013 .

[17]  Susana Ferreiro,et al.  A Context-Aware Oil Debris-Based Health Indicator for Wind Turbine Gearbox Condition Monitoring , 2019, Energies.

[18]  Ming Liang,et al.  Extraction of oil debris signature using integral enhanced empirical mode decomposition and correlated reconstruction , 2011 .

[19]  Wei Li,et al.  Inductive debris sensor using one energizing coil with multiple sensing coils for sensitivity improvement and high throughput , 2018, Tribology International.

[20]  Shaoping Wang,et al.  Radial inductive debris detection sensor and performance analysis , 2013 .

[21]  Saheeb Ahmed Kayani,et al.  Using combined XRD-XRF analysis to identify meteorite ablation debris , 2009, 2009 International Conference on Emerging Technologies.

[22]  Dingxin Yang,et al.  Theoretic analysis and numerical simulation of the output characteristic of multilayer inductive wear debris sensor , 2012, Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing).

[23]  Yu Wu,et al.  Determination of metal particles in oil using a microfluidic chip-based inductive sensor , 2016 .