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The online monitoring of metal particles in lubricating oil plays an important role in equipment fault diagnosis technology. This paper designs an online wear monitoring warning sensor based on the electromagnetic induction of metal particles in lubricating oil. First, different from the traditional three-coil sensing and detection method, the sensor consists of two excitation coils and one detection coil. In addition, the parallel capacitance and detection capacitance parameters are obtained by COMSOL’s scanning frequency, and the best detection capacitance is 7.53 nF. Second, according to the obtained optimal detection parallel capacitance value, the amplitude data of the particle signal, as well as the ferromagnetic particles above 60 µm and the non-ferromagnetic particles above 80 µm, are obtained. Third, according to the principle of three-coil induction, a mapping relationship model was established between the size range of metal wear particles in lubricating oil. Finally, we set up an oil wear particle platform to verify the sensor performance. The ferromagnetic and non-ferromagnetic particles are divided into multiple size ranges, and the peak-to-peak values of the output signal of different-sized wear particles are measured. We developed a prototype sensor and verified the signal consistency and repeatability of the sensor to wear metal particles. In addition, we used the sensor to test a large number of metal particles of different sizes (14 ferromagnetic particle standard samples with particle sizes ranging from 20.64 to 457.59 µm and ten non-ferromagnetic particle standard samples with particle sizes ranging from 40.52 to 348.07 µm). The experimental results show that the sensor can directly achieve monitoring sensitivity for ferromagnetic particles greater than 64.57 µm and non-ferromagnetic (copper) particles greater than 82.83 µm under the 4.2 mm aperture flow channel. The sensor can effectively realize the sensitivity on monitoring of small ferromagnetic particles and non-ferromagnetic particles, and it is particularly sensitive to small non-ferromagnetic particles.

Characterizing the operational wear status of mechanical equipment based on online monitoring of metal particles in lubricating oil plays a significant role in the effect of equipment fault diagnosis technology. According to the theoretical analysis of the electromagnetic induction principle and Biot–Savart’s law, combined with the finite element simulation analysis, systematic study and analysis were conducted on the distribution of magnetic field inside a single inductance coil, the coupling relationship between metal particles in lubricating oil, and the inductance coil. This paper analyzed the effects of four important design parameters that were the excitation frequency, the inside diameter of the coil, the turns number of the coil, and the length of the coil. On magnetic field uniformity and monitoring sensitivity, experiments demonstrated that: the correlation between the uniformity of the magnetic field on the testing surface of the sensor inductance coil and the coil radius and length is the highest, followed by the correlation with the number of coil turns. The correlation with the excitation frequency can be ignored in a negligible manner. In addition, experimental results indicated that if the ratio between the inside diameter of the inductance coil and the length of the coil (R/L) was less than 0.41, the magnetic field uniformity would reach over 91%. Meanwhile, results showed that the sensitivity of the sensor to ferromagnetic and non-ferromagnetic particles increased with the decrease in the coil inner diameter and inductance and increased with the increase in the excitation frequency. There is a specific length that can make the sensor coil monitoring, which is the most sensitive.