A Method for Aliasing Metal Particle Recognition Based on Three-Coil Sensor Using Frequency Conversion

The diesel engine on a ship is crucial as it serves as the primary power source, significantly influencing both the vessel’s efficiency and safety. Monitoring metal wear particles found in lubricating oil is essential for assessing the lubrication condition of mechanical equipment onboard and anticipating potential failures. Analyzing these metal wear particles allows us to gauge the wear status of bearing pairs within the machinery, thereby providing a technical foundation for routine maintenance activities. However, under real operating conditions, it can be challenging to prevent multiple metal particles from simultaneously passing through sensors. To address this issue, this research introduces an innovative three-coil induction sensor that employs a variable-frequency excitation technique to explore how induction and eddy currents interact. The findings indicate that when the excitation frequency changes, the peak value of the signal from 337 μm iron particles only increases by 3.35 times, while the peak value of the signal from 340 μm copper particles increases by 22.69 times. Consequently, this study recommends using changes in excitation frequency to differentiate between mixed metal particles made of various materials.