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Research on Detection Performance of Four-Coil Inductive Debris Sensor

Xinhang Shen, Qingpeng Han, Yu Wang, Bin Wu, Rui Zhu

2023IEEE Sensors Journal17 citationsDOI

Abstract

The online monitoring of debris in oil can timely and accurately reflect the wear status of mechanical equipment. The inductive debris sensor based on the electromagnetic induction can effectively detect various parameters of debris. The four-coil structure-based of the sensor is theoretically introduced. The optimal coil length, the turns of the excitation coil, and the turn ratio are obtained through simulation to improve the sensitivity of the inductive debris sensor. The effects of the excitation frequency and the movement velocity, size, position, and material of the debris on the sensor output are investigated. The sensing signal recovered by coherent demodulation confirms the sensor’s effectiveness in identifying metal debris. The experiment realized the identification of iron debris with a diameter of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$93.5 \mu \text{m}$ </tex-math></inline-formula> and copper debris with a diameter of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$447.3 \mu \text{m}$ </tex-math></inline-formula> under the 3 mm pipe radius, providing a reference for the design of four-coil inductive debris sensor.

Topics & Concepts

Electromagnetic coilInductive sensorDebrisCoil springElectromagnetic inductionInductive reasoningAcousticsComputer sciencePhysicsElectrical engineeringMechanical engineeringEngineeringArtificial intelligenceMeteorologySpring (device)Non-Destructive Testing TechniquesLubricants and Their AdditivesWelding Techniques and Residual Stresses