The presence of ferrous wear debris in lubricating oil may cause progressive damage in the internal combustion engines. Online monitoring of the size and concentration of these particles in the oil is a way to optimize the engine performance and its life cycle.
In this study, an online sensor was designed and fabricated to identify ferrous wear particles in the engine oil based on the induction method. The diameter of the sensor outlet duct was designed as small as possible to generate a high-intensity magnetic induction and achieve a proper sensitivity in the sensor. The experiments were designed and performed in offline mode. Furthermore, to evaluate the actual performance of the sensor in presence of iron particles in the oil, online tests were performed at different sizes and concentrations.
It was concluded from offline tests that the highest sensitivity of the sensor occurs at the frequency and voltage of 2.5 kHz and 120 V, respectively. According to the results of the online tests, the larger the particle size, the higher the peaks at the sensor output. Also, a high density of the peaks was observed in the sensor output graphs as the concentration of particles was increased.
The proposed sensor was able to identify ferrous wear particles larger than 125 µm separately, which is the failure limit in the internal combustion engines.
The authors would like to express their gratitude to Dina Motors Company® for their support of this research.
Talebi, A., Hosseini, S.V., Parvaz, H. and Heidari, M. (2021), "Design and fabrication of an online inductive sensor for identification of ferrous wear particles in engine oil", Industrial Lubrication and Tribology, Vol. 73 No. 4, pp. 666-675. https://doi.org/10.1108/ILT-12-2020-0439
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