An Inductive Sensor with a Biased Magnetic Field to Distinguish Wear Debris by Magnetism and Conductivity

Inductive wear debris sensors are an indispensable tool for real-time wear monitoring. Traditionally, these sensors contain only one type of magnetic field, time harmonic or static, and so cannot avoid the contradiction between magnetization and eddy current, resulting in limited performance. In this article, a detection method based on the biased magnetic fields is proposed for the first time, which can surpass this limitation in the traditional sensors. By coupling high-gradient biased static and high-frequency time-harmonic fields, the proposed sensor has the capability to enhance the precision of detecting both magnetic and nonmagnetic conductive particles simultaneously. In the following, the corresponding detection principle and mathematical model are presented, and relevant simulations are provided. Theoretical and simulation analysis illustrates the principle behind and the advantage of our work. Moreover, a signal processing system is developed to support the sensor testing. Experiments with different particle sizes and materials are carried out. The proposed sensor can identify a 50 μm copper particle and a 50 μm iron particle within a 4 mm diameter pipe, and the induction signal is linear with the volume of wear debris. The proposed method offers a new idea for inductive wear debris sensing, with great potential for higher accuracy and wider application scenarios.