The effect analysis of the excitation frequency on the output signal of an inductive sensor for the detection of wear debris in lubrication oil

The inductive sensor has found a wide application in the wear fault real-time monitoring, the excitation frequency setting plays a significant role in the detection of the debris size, especially for various material debris. In this work, the mathematic model of a three-coil inductive sensor is presented, and the finite element simulation model is established to explore the effect of the excitation frequency on the output signal of a sensor. An experimental platform is set up to verify the influence rules acquired by the finite element analysis and the detection ability for various engineering material debris. The experimental results show that the effectiveness of the influence rules and provide a beneficial reference for the design of an inductive sensor. By studying the output signal of the sensor under different frequencies, the optimal excitation frequency is determined, which makes the monitoring effect of the sensor more accurate and reliable. Using the excitation frequency, the sensor is designed to monitor the wear of parts of different materials, improve the effectiveness of monitoring, and realize the monitoring of different materials. The verification experiment is based on the friction and wear experiment platform to simulate a variety of working conditions, and the materials selected are from vulnerable parts of large complex rotating machinery equipment, which has practical engineering application value.