A Bridge-Type Inductance Sensor With a Two-Stage Filter Circuit for High-Precision Detection of Metal Debris in the Oil

Xie, Yucai; Shi, Haotian; Zhang, Hongpeng; Yu, Shuang; Ilerioluwa, Lebile; Zheng, Yiwen; Li, Guobin; Sun, Yuqing; Chen, Haiquan

doi:10.1109/jsen.2021.3085361

Cited by 16 publications

(5 citation statements)

References 25 publications

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“…In the inductive detection method, the number of coils used can be divided into single-coil oil detection sensors [5][6][7][8], dual-coil oil detection sensors [9,10], and three-coil oil detection sensors [11][12][13][14]. The single-coil abrasive particle detection sensor mainly uses a single coil for detection.…”

Section: Intorductionmentioning

confidence: 99%

Mixed metal differentiation method using microfluidic oil detection sensors

Xie,

Shi,

Zhang

2024

J. Phys.: Conf. Ser.

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This paper analyzes the characteristics of iron particles and copper particles in the alternating magnetic field with the change of excitation frequency, and proposes a method of using microfluidic oil detection sensor to achieve the distinction of mixed metals. The magnetic field strength of the coil is changed by changing the excitation frequency, which in turn makes the metal particles of different materials act with different strengths in the magnetic field, and realizes the accurate detection of the particles. In the article, firstly, the magnetization effect of the particles in the alternating magnetic field is simulated by the simulation software, the change of the magnetization effect with frequency is simulated, and the change curve of the inductance signal when the particles pass is obtained. Then the experimental verification is carried out by building a test bench, and the experimental results are consistent with the simulation results, which all confirm the feasibility of realizing the detection of aliased particles by frequency conversion. The method provides a new reference direction for the precise and accurate detection of oil detection technology, and has good research value.

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Section: Intorductionmentioning

confidence: 99%

Mixed metal differentiation method using microfluidic oil detection sensors

Xie,

Shi,

Zhang

2024

J. Phys.: Conf. Ser.

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“…Although the SGMD decomposition method has proven to be effective in enhancing the sensitivity of the inductive abrasive sensor, there remain unresolved challenges pertaining to the calculation speed and end effects associated with this method. Xie et al conducted an investigation on a bridge-type inductive wear particle detection sensor that incorporates a secondary filter circuit in 2021 [60]. The sensor configuration comprises a dual solenoid coil, a Wheatstone bridge structure sensing unit, and a secondary filter circuit.…”

Section: Inductive Sensormentioning

confidence: 99%

A Critical Review of On-Line Oil Wear Debris Particle Detection Sensors

Han,

Mu,

Liu

et al. 2023

JMSE

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In the field of marine engineering, the friction and wear experienced by rotating mechanisms are recognized as significant contributors to the failure of marine machinery. In order to enhance the safety and dependability of marine ship operations, the implementation of on-line oil wear debris particle detection sensors enables the on-line monitoring of oil and facilitates the rapid identification of abnormal wear locations. This paper provides a critical review of the recent research progress and development trends in the field of sensors for on-line detection of oil wear debris particles. According to the method of sensor detection, wear debris particle detection sensors can be classified into two distinct categories: electrical and non-electrical sensors. Electrical sensors encompass a range of types, including inductive, capacitive, and resistive sensors. Non-electrical sensors encompass a range of technologies, such as image processing sensors, optical sensors, and ultrasonic sensors. Finally, this review addresses the future research directions for wear debris particle detection sensors in light of the challenging problems currently faced by these sensors.

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“…When the particles pass through the coil to generate an inductive signal, the two arms of the bridge generate a voltage difference [34], the voltage of the two arms are rectified into two DC pulsating voltage signals, and then filtered by the filter circuit to remove the high frequency noise signal [35], interspersed in the particle signal, and finally differentially amplified by an amplifier circuit to generate the differential voltage caused by the particles.…”

Section: Design and Principle Analysis Of Inductor Bridgementioning

confidence: 99%

Analysis of the Effect of Velocity on the Eddy Current Effect of Metal Particles of Different Materials in Inductive Bridges

Zhang

et al. 2022

Sensors

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A method for analyzing the influence of velocity changes on metal signals of different materials in oil detection technology is proposed. The flow rate of metal contaminants in the oil will have a certain impact on the sensitivity of the output particle signal in terms of electromagnetic fields and circuits. The detection velocity is not only related to the sensitivity of the output particle signal, but also to the adaptability of high-speed and high-throughput in oil online monitoring. In this paper, based on a high-sensitivity inductive bridge, the eddy current effect of velocity in a time-harmonic magnetic field is theoretically analyzed and experimentally verified, the phenomenon of particle signal variation with velocity for different materials is analyzed and discussed, and finally the effect of velocity on the output signal of the processing circuit is also elaborated and experimentally verified. Experiments show that under the influence of the time-harmonic magnetic field, the increase of the velocity enhances the detection sensitivity of non-ferromagnetic metal particles and weakens the detection sensitivity of non-ferromagnetic particles. Under the influence of the processing circuit, different velocities will produce different signal gains, which will affect the stability of the signal at different velocities.

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A Bridge-Type Inductance Sensor With a Two-Stage Filter Circuit for High-Precision Detection of Metal Debris in the Oil

Cited by 16 publications

References 25 publications

Mixed metal differentiation method using microfluidic oil detection sensors

Mixed metal differentiation method using microfluidic oil detection sensors

A Critical Review of On-Line Oil Wear Debris Particle Detection Sensors

Analysis of the Effect of Velocity on the Eddy Current Effect of Metal Particles of Different Materials in Inductive Bridges

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