An online wear metal particles monitoring warning sensor based on electromagnetic induction in lubricating oil

Abstract

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.