Triple-coil Sensor Design for Metal Abrasive Particle Detection in Oil

doi:10.3901/JME.2025.12.050

Abstract

Abstract: When the mechanical system works, due to the interaction of the mechanical unit, its internal will produce different degrees of wear, the generation of abrasive particles will flow around with the oil, if not detected in a timely manner will exacerbate the wear process, affecting the service life of the entire mechanical system. The metal abrasive particles in the oil contain rich tribological information, and their material and particle size are important reference values for judging the operation status of mechanical equipment. To achieve the differentiated detection of metal abrasive particles in oil, this designs a triple-coil sensor with both flux and detection accuracy, which adopts an integrated digital phase-locked board for the excitation signal and data acquisition with a high integration degree. The sensor design and performance testing are carried out from three aspects, namely, form factor packaging, magnetic field simulation, and experimental verification, respectively, and the particle profiles obtained from the simulation are consistent with the experimental results. Iron and copper particles with different particle sizes were tested, and theoretical calculations showed that the sensor can achieve the detection of iron particles with a minimum size of 23 μm and copper particles with a minimum size of 50 μm. This triple-coil sensor provides a new idea for the development of portable abrasive particle detection equipment.

Key words: triple-coil sensor, oil detection, inductance detection, wear particle detection, phase-locked amplification

CLC Number:

TP212
TH73

XIE Yucai, HU Shukui, BAI Chenzhao, SHI Haotian, ZHANG Hongpeng. Triple-coil Sensor Design for Metal Abrasive Particle Detection in Oil[J]. Journal of Mechanical Engineering, 2025, 61(12): 50-59.

References

[1] 石新发，贺石中，谢小鹏，等. 摩擦学系统润滑磨损故障诊断特征提取研究综述[J]. 摩擦学学报，2023，43(3)：241-255. SHI Xinfa，HE Shizhong，XIE Xiaopeng，et al. Review on feature extraction of lubrication and wear fault diagnosis in tribology system[J]. Tribology，2023，43(3)：241-255.
[2] FAN Bin，LI Bo，FENG Song，et al. Modeling and experimental investigations on the relationship between wear debris concentration and wear rate in lubrication systems[J]. Tribology International，2017，109：114-123.
[3] 白晨朝，汪承杰，王笑天，等. 基于高梯度磁场结构电感式油液污染物检测传感器研究[J]. 机械工程学报，2022，58(23)：98-105. BAI Chenzhao，WANG Chengjie，WANG Xiaotian，et al. Research on inductive oil contaminant detection sensor based on high gradient magnetic field structure[J]. Journal of Mechanical Engineering，2022，58(23)：98-105.
[4] 史皓天，张洪朋，谢雨财，等. 一种基于微流体制备的电阻-电感式磨粒传感器[J]. 中国机械工程，2022，33(20)：2468-2475. SHI Haotian，ZHANG Hongpeng，XIE Yucai，et al. A resistance-inductance debris sensor based on microfluidic fabrication[J]. China Mechanical Engineering，2022，33(20)：2468-2475.
[5] 史皓天，张洪朋，顾长智，等. 电感-电容双模式液压油污染物检测传感器[J]. 机械工程学报，2020，56(2)：20-26. SHI Haotian，ZHANG Hongpeng，GU Changzhi，et al. Inductance-capacitance dual mode sensor for the detection of contaminants in hydraulic oil[J]. Journal of Mechanical Engineering，2020，56(2)：20-26.
[6] 曾周末，许恩蕾，黄新敬，等. 高灵敏低压电磁感应式滑油磨屑传感器[J]. 仪器仪表学报，2022，43(2)：1-9. ZENG Zhoumo，XU Enlei，HUANG Xinjing，et al. High-sensitivity，low-voltage lubricating oil wear debris sensor based on electromagnetic induction[J]. Chinese Journal of Scientific Instrument，2022，43(2)：1-9.
[7] 李业辉，宁致远，薛邴森，等. 基于电感式传感器的金属颗粒材质识别及粒径估计[J]. 仪器仪表学报，2021，41(8)：24-33. LI Yehui，NING Zhiyuan，XUE Bingsen，et al. Metal particle material identification and size estimation based on the inductive sensor[J]. Chinese Journal of Scientific Instrument，2021，41(8)：24-33.
[8] 萧红，周威，罗久飞，等. 一种高梯度静磁场感应式全流量磨粒监测传感器[J]. 仪器仪表学报，2020，41(6)：10-18. XIAO Hong，ZHOU Wei，LUO Jiufei，et al. An inductive sensor based on the high-gradient static magnetic field for full flow debris monitoring[J]. Chinese Journal of Scientific Instrument，2020，41(6)：10-18.
[9] 罗久飞，郑睿，王鑫宇，等. 油液磨粒感应电压特征辨识研究[J]. 仪器仪表学报，2022，43(8)：173-181. LUO Jiufei，ZHENG Rui，WANG Xinyu，et al. Study on feature identification of oil debris induced voltages[J]. Chinese Journal of Scientific Instrument，2022，43(8)：173-181.
[10] 李海青，刘伟，冯松，等. 感应式磨粒检测传感器信号特征提取方法研究[J]. 电子测量与仪器学报，2022，36(12)：1-9. LI Haiqing，LIU Wei，FENG Song，et al. Research on signal feature extraction for inductive debris detection sensor[J]. Journal of Electronic Measurement and Instrumentation，2022，36(12)：1-9.
[11] 苏连成，王航. 润滑油磨粒在线检测系统的设计与实现[J]. 仪表技术与传感器，2019(1)：100-105. SU Liancheng，WANG Hang. Design and realization of on-line inspection system for oil debris[J]. Instrument Technique and Sensor，2019(1)：100-105.
[12] 王志娟，赵军红，丁桂甫. 新型三线圈式滑油磨粒在线监测传感器[J]. 纳米技术与精密工程，2015，13(2)：154-159. WANG Zhijuan，ZHAO Junhong，DING Guifu. A novel online oil debris monitoring sensor with three coils[J]. Nanotechnology and Precision Engineering，2015，13(2)：154-159.
[13] ZHENG Yuan，SONG Feng，JUN Tan，et al. A passive ferro-particle sensor of lube-oil based on single permanent magnetic ring[J]. IEEE Sensors Journal，2022，22(9)：8565-8573.
[14] YIN Yibing，ZHANG Qiang，FENG Long，et al. A wear debris recognition method based on dual-channel electrostatic signal and prominence of cross-correlation function[J]. Tribology International，2023，190：109020.
[15] 史皓天，张洪朋，马来好，等. 高精度双线圈式磨粒传感器的设计及研究[J]. 机械工程学报，2021，57(2)：39-45. SHI Haotian，ZHANG Hongpeng，MA Laihao，et al. Design and research of high sensitivity double-coil wear debris sensor[J]. Journal of Mechanical Engineering，2021，57(2)：39-45.
[16] 牛泽，李凯，白文斌，等. 电感式油液磨粒传感器系统设计[J]. 机械工程学报，2021，57(12)：126-135. NIU Ze，LI Kai，BAI Wenbin，et al. Design of inductive sensor system for wear particles in oil[J]. Journal of Mechanical Engineering，2021，57(12)：126-135.
[17] XIE Yucai，ZHANG Yuwei，ZHANG Hongpeng，et al. Design of a micro-triple-coil multi-pollutant detection sensor based on high-gradient magnetic field[J]. Sensors and Actuators：A. Physical，2022，362：114661.
[18] ZHENG Changsong，XU Wang，REN Jia，et al. Study on the sensitivity of detachable wear particle sensor based on iron-based amorphous soft magnetic rings[J]. IEEE Sensors Journal，2022，22(13)：12708-12718.
[19] QIAN Min，REN Yijun，FENG Zhihua. Wear Debris sensor using intermittent excitation for high sensitivity，wide detectable size range，and low heat generation[J]. IEEE Transactions on Industrial Electronics，2022，70(6)：6386-6394.
[20] LI Kai，BAI Wenbin，LI Yuan，et al. Online symmetric magnetic excitation monitoring sensor for metal wear debris[J]. IEEE Sensors Journal，2022，22(6)：5571-5579.
[21] SONG Feng，YANG Leilei，FAN Bin，et al. A ferromagnetic wear particle sensor based on a rotational symmetry high-gradient magnetostatic field[J]. IEEE Transactions on Instrumentation and Measurement，2020，70：9504709.
[22] QIAN Min，REN Yijun，FENG Zhihua. Interference reducing by low-voltage excitation for a debris sensor with triple-coil structure[J]. Measurement Science and Technology，2019，31(2)：025103.
[23] SONG Feng，YANG L，QUI G，et al. An inductive debris sensor based on a high-gradient magnetic field[J]. IEEE Sensors Journal，2019，19(8)：2879-2886.
[24] REN Yijun，ZHAO G F，QIAN M，et al. A highly sensitive triple-coil inductive debris sensor based on an effective unbalance compensation circuit[J]. Measurement Science and Technology，2018，30(1)：015108.
[25] REN Y J，LI W，ZHAO G F，et al. Inductive debris sensor using one energizing coil with multiple sensing coils for sensitivity improvement and high throughput[J]. Tribology International，2018，128：96-103.
[26] 赵凯华，陈熙谋．电磁学[M]. 北京：高等教育出版社，2006． ZHAO Kaihua，CHEN Ximou. Electromagnetics[M]. Beijing：Higher Education Press，2006．
[27] LI Du，JIANG Zhe. An integrated ultrasonic-inductive pulse sensor for wear debris detection[J]. Smart Mater. Struct.，2013，22(2)：025003.